RIGHT FACULTY PROJECT

Learning to model geophysical processes with NNs

Academic Program: Earth Science and Engineering

Scientific machine learning (SML) is an emerging field focused on leveraging machine learning across different sciences whose natural processes are governed by well-established physical equations. Early successes have been reported by the geophysical community in terms of modelling various wave phenomena by means of PINNS, e.g. eikonal equation (bin Waheed et al., 2021) and wave equation (Alkhalifah et al., 2021). Alternative solutions have recently emerged in the SML community with the aim of overcoming some of the limitations of PINNs and extending applicability from functionals to operators. This project will investigate such approaches in the context of geophysical modelling and inversion and identify the benefits and limitations when compared to traditional modelling methods as well as PINNs. References: - U. bin Waheed, E. Haghighat, T. Alkhalifah, C Song, Q Hao, 2021, PINNeik: Eikonal solution using physics-informed neural networks, Computers & Geosciences. - T. Alkhalifah, C. Song, U. Waheed, Q. Hao, 2021, Wavefield solutions from machine learned functions, arXiv preprint arXiv:2106.01433.

BAS/1/1414-01-01

matteo.ravasi@kaust.edu.sa

geophysics; modelling; machine learning;

Geophysics

The candidate will be tasked with: - Literature review of ML methods for learning physical phenomena governed by PDEs. - Develop and implement one of the methods for a geophysical PDE of choice. - Compare pros and cons of the developed method against state-of-the art numerical modelling methods and PINNs.

Earth Science and Engineering

Physical Sciences and Engineering

Undergraduate

Resilient Models for Attacks Detection in Cyber-Physical Systems

Academic Program: Electrical Engineering

The goal of this project is developing methods to merge Machine Learning (ML) with physics-based models to create control algorithms can significantly enhance the resiliency of Cyber-Physical Systems (CPS). The approach will combine recent results in ML with control theory via constrained optimization to create novel systems and methods for protecting CPS from malicious cyber intruders via detection and prevention strategies. Specifically, the research project focuses on (1) refining the offline/online training and execution algorithms of ML models through physics-based constrained optimization, (2) developing secure estimation and control algorithms that are significantly more resilient to cyber-attacks than the state-of-the-art counterparts, and (3) improving the distributed resiliency for networked systems supporting multi-agent autonomous systems.

BAS/1/1692-01-01

charalambos.konstantinou@kaust.edu.sa

Cyber-physical systems, resiliency, cybersecurity, control methods, machine learning, physics-based methods.

Electrical and Computer Engineering/Computer Science

The goal of this internship is to analyze and improve existing data-driven and physics-based algorithms for attack detection in CPS. The student will be expected to learn about existing solutions, as well as the challenges and requirements to applying such techniques in their settings. With guidance of other team members, the student will then find new solutions for improving algorithmic resiliency in order to reduce cyber-risks related to the CPS operation. Candidates should be motivated to work on research-oriented problems with a team and develop new solutions. They should have a strong background in controls, in particular with regards to machine learning and power systems. They are also expected to be proficient in MATLAB/Simulink.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Real-Time (co-)Simulation for Cybersecurity

Academic Program: Computer Science

The objective of this project is to use Real-Time Simulation (RTS) and co-simulation models for real-time prediction and control of disturbances related with attacks propagation. Essentially, the goal is to study how RTS via real-time communication interfaces of different RTS tools can run systems security, resilient and isolation algorithms in order to monitor and control the system under study.

BAS/1/1692-01-01

charalambos.konstantinou@kaust.edu.sa

Real-time simulation, cybersecurity, attacks, detection, prevention.

Electrical and Computer Engineering/Computer Science

The goal of this project is to develop and implement models in RTS using OPAL-RT hardware and software to study how cyber-attacks effects can propagate in real-time and investigate controls able to isolate such impact. Students should have backgrounds and experience using real-time simulators software such as RT-LAB, HYPERSIM, RSCAD, etc.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Regaining Trust in IoT

Academic Program: Computer Science

While embedded devices play an increasingly significant role in the functional interoperability and coordination of various IoT systems, they are often developed without security in mind. The premise of this research is that effective security solutions can benefit from assistance by a trustworthy hardware root of trust. This research involves approaches that utilize device intrinsic (non-)silicon-based physical/hardware characteristics to verify, authenticate, and trust IoT devices. The goal is for such methods is to support and improve detection of security breaches in the device, network, or/and system level within critical information infrastructures. This can be achieved by leveraging the acquired hardware-level values in order to verify the integrity of each layer in a single device as well the integrity of the process variables within a control operation.

BAS/1/1692-01-01

charalambos.konstantinou@kaust.edu.sa

IoT, security, embedded systems, hardware security.

Computer Science and Engineering

1. Experimental evaluation of an existing hardware-based security approach. 2. Design and implementation of an improved approach incorporating a mixture of hardware signals: build an intrusion detection model capturing any malicious activity in any layer of the system stack.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Cyber-Secure Integration of Renewable Energy Sources

Academic Program: Electrical Engineering

This research project aims to contribute towards a resilient and secure power system employing power electronics for renewable energy sources (RES) integration. The goal is to examine the security implications of integrity and availability attacks in power transmission and distribution systems, and examine the performance and economic impact on real-time energy market operations. Risk assessment methodologies will quantify attack resources under certain level of adversarial knowledge. The objective is to enhance system cyber-(resiliency, security), while addressing disruptive cyber-physical events and preventing these effects from escalating into major failures and hence causing cascading blackout scenarios.

BAS/1/1692-01-01

charalambos.konstantinou@kaust.edu.sa

Renewable energy, cybersecurity, power electronics, prevention, cyber-physical energy systems.

Electrical and Computer Engineering/Computer Science

1. Improve an existing power system benchmark to support certain RES and their corresponding controllers. 2. Impact evaluation of attacks at the various connection points. 3. Examine effects of attacks on market operations. 4. Identify methods to improve system performance.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Ransomware in Industrial Control Systems

Academic Program: Computer Science

According to a recent report, ransomware attacks on industrial entities increased more than 500% from 2018 to 2020. What is more, in 2020, ransomware, targeted ransomware, supply chain breaches and cloud connectivity all emerged as top-of-mind concerns for security teams at industrial enterprises. One of the biggest cyberattacks in history – the SolarWinds Orion supply chain breach – impacted as many as 18,000 organizations, many of which were industrial enterprises with physical operations. As a result, this project will study effective defense-in-depth security strategies, ensure an understanding of network interdependencies, and conduct crown jewel analysis to identify potential weaknesses that could disrupt business continuity and production in the event of ransomwares.

BAS/1/1692-01-01

charalambos.konstantinou@kaust.edu.sa

Ransomware, industrial control systems, cybersecurity, critical infrastructure.

Computer Science and Engineering

In this project, the students will examine the security issues of supply chain ransomware in industrial control systems (ICS) environments. One direction would be to investigate the applicability of unidirectional gateway technology to provide robust protection from such targeted attacks. Other methods include investigation of deep learning malware detector indicators.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Physiology of corals from Red Sea reef flats

Academic Program: Marine Science

Corals play an integral part in the health of the oceans as ecosystem engineers, building highly diverse and large reef systems. However, rapid increases in natural and human-induced stressors mean that coral reefs are under more pressure than ever and are declining rapidly. In particular, increases in sea surface temperature threaten the functioning of the coral holobiont (the coral host plus its associated microbes). In order to better understand how corals will perform in warmer seas, this study will assess coral physiology across a temperature gradient in the central Red Sea, where some coral colonies are inhabiting high-temperature reef flats that serve as analogs to future ocean conditions. In particular, this project aims to evaluate total energy reserves (lipid, protein, and carbohydrate content) of corals across this temperature gradient from several reefs near KAUST. This project will focus, among others, on the following research questions: 1. Are there significant differences in total energy reserves of corals from sites experiencing different temperature ranges? 2. What are the seasonal differences in total energy reserves, and does season attenuate/magnify differences between sites? This position will primarily assist with extraction and quantification of lipids, protein and carbohydrates of samples in the laboratory. Assistance with sample collection in the field is also possible. As all of the colonies inhabit shallow water and are sampled via snorkeling, SCUBA certification is not required for this fieldwork. Due to the COVID-19 pandemic, all VSRP students are required to be fully vaccinated before arrival. Please refer to the VSRP webpage for more information.

BAS/1/1010-01-01

Walter.richiv@kaust.edu.sa

Coral; Coral reefs; Physiology; Thermal tolerance

Coral physiology

The project is intended to assist with a PhD thesis exploring coral holobiont functioning across thermal gradients in the Red Sea. The goal is to have a peer-reviewed publication, in which the student would be a co-author.

Marine Science

Biological and Environmental Sciences and Engineering

Undergraduate

Red Sea Research Center

Machine learning techniques for divergence-free field reconstruction

Academic Program: Applied Mathematics and Computer Science

The student will work on machine learning techniques applied to the study of divergence-free flow reconstruction. Specifically, the student will use different Neural Network architectures and training algorithms to reconstruct a divergence-free flow from sparse and noisy data. The student will also investigate the spectral properties of the reconstructed flow and use this information to improve the training algorithm. They will test the methods on several problems and compare results with existing methods. We will meet weekly during the duration of the project.

BAS/1/1604-01-01

raul.tempone@kaust.edu.sa

Machine Learning, Deep Neural Networks, Dynamical Systems, Numerical Analysis, Stochastic Numerics

Machine learning

As the main project deliverable, we expect a scientific report describing the methodology developed in the internship and its numerical use in various applications. The working environment the student will use should include a GIT repository for all project-related materials to facilitate proper verification processes. These materials include, among others, the codes and the saved input-outputs corresponding to all tested cases.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Graduate

Concentrated Solar Thermal Energy for Mineral Processing

Academic Program: Mechanical Engineering

This research project will assess the efficacy of using concentrated solar thermal energy in processing mineral ores. Students will have the choice to work on: 1. Low carbon calcination of Limestone and Clay for Cement production 2. Use of solar energy for Ore shock pretreatment to reduce comminution energy 3. Renewable steam for ores calcination through H2/O2 combustion Most projects will involve both experimental and computational research.

BAS/1/1411-01-01

bassam.dally@kaust.edu.sa

Solar, Renewable, Energy, Combustion, Mechanical, Engineering

Renewable Energy

1. Parametric study to quantify effect of solar concentration, temperature, type of ore, size of particles etc.. 2. System level analysis to assess the different aspects that make it techno-economically viable 3. Design, build and test hybrid combustion of renewable fuels and solar thermal for mineral processing

Mechanical Engineering

Physical Sciences and Engineering

Graduate

Clean Combustion Research Center

A Machine Learning Approach to Unentangle Wetting

Academic Program: Chemical Engineering

Academic Program: Environmental Science and Engineering

Liquid-repellent surfaces are utilized in a wide spectrum of practical applications, including anti-fogging coatings, reducing frictional drag, water desalination, separating alcohols and other volatile organics from fermenter broths, and beyond. The most common criteria for quantifying their liquid-repellence are based on measuring apparent contact angles – advancing and receding– of sessile droplets of probe liquids placed onto them. Of these, the receding contact angles provide crucial information about the chemical or topographical make-up of the surface. However, despite over two centuries of research on contact angles, there are no well-established theories for predicting receding contact angles, for instance, as a function of the surface micro/nano (hierarchical) texture and chemical make-up and the speed of the liquid front. Here, we propose to assess the efficacy of a Machine Learning approach towards predicting receding contact angles from surface roughness features. We aim to design and evaluate a neural network architecture for automatic inference of dynamic wetting properties including advancing and receding contact angles at various speeds, surface topography and chemical make-up, and drop size and volume. Subsequent analysis of model parameters can point to key surface features that contribute to changes in the output variable, which can help advance our fundamental understanding of wetting of complex surfaces, implicit in water science and technology.

BAS/1/1070-01-01

himanshu.mishra@kaust.edu.sa

machine learning, microstructures, wetting

machine learning, microstructures, wetting

The intern student will be tasked with: 1. Collecting a dataset of images of hierarchically textured natural surfaces and micro/nano fabricated surfaces, labeled with static and dynamic wetting properties and chemical composition. 2. Helping design and implement a neural network architecture, optimized for the prediction of apparent contact angles on hierarchical surfaces (e.g., mico, nano, or mili meter scale). Project-duration will be 3-6 month, and the student arrival/departure dates will be discussed.

Chemical Engineering

Biological and Environmental Sciences and Engineering

Undergraduate

Water Desalination and Reuse Center

Electro-catalyzed C-C and C-X bond cross-couplings

Academic Program: Chemical Science

The development of sustainable and scalable catalytic methodologies to access structurally diverse organic compounds is a long-term aim for organic chemists. In this regard, organic electrocatalysis has been developed as an attractive catalytic platform making use of renewable electricity instead of stoichiometric oxidants or reductants. We are focusing on the construction of new C-C and C-X bonds and their mechanistic studies under electrochemical conditions with or without the aid of metal catalyst. Project-duration will be 3-6 month, details of arrival/departure dates to be discussed.

BAS/1/1385-01-01

chen.zhu@kaust.edu.sa

Electro-catalyzed, C-C bond formation, C-X bond cross-couplings, Electrocatalysis

Chemistry, Electrocatalysis

​Students shall extend their general knowledge and skills in chemistry, and electrocatalysis. An emphasis will be put on electrocatalysis steps and techniques. Students will be taught to work independently on projects, yet strengthening their critical sense to develop new ideas. In the course of the internship students shall demonstrate this understanding during oral presentations and one final written report.

Chemical Science

Physical Sciences and Engineering

Undergraduate

KAUST Catalysis Center

Expediting surface wave dispersion curve picking with ML

Academic Program: Earth Science and Engineering

Surface waves carry useful information about the subsurface, especially of the shear-wave velocities in the near subsurface (upper 100s of meters). Techniques such as the Multichannel analysis of surface waves have been successfully applied in many geological settings on both active and passive seismic recordings. Despite its maturity and ease of use, MASW requires the picking of dispersion curves from dispersion panels; this task is generally automated (eg Allmark), however it requires QC that can be very time consuming. In this project, we aim to investigate the use of deep learning techniques for the field of computer vision to accomplish this task. More specifically, we will train a neural network to learn the direct mapping from the seismic data to their associated dispersion curve by-passing the creation and picking of dispersion panels. The accuracy of our method will be evaluated on both synthetic and real datasets.

BAS/1/1414-01-01

matteo.ravasi@kaust.edu.sa

Geophysics, Machine Learning, Surface Waves

Geophysics

The candidate will be tasked with: - Creating synthetic datasets containing surface waves using different modeling techniques (analytical solutions, FD-modelling, FE-modelling). - Develop a Machine Learning modelfor the automatic picking of dispersion curves directly from seismic data and compare its performance with other state-of-the-art methods that require picking on dispersion panels - Apply the newly developed method to a field dataset (e.g., USArray)

Earth Science and Engineering

Physical Sciences and Engineering

Graduate

Machine Learning and Dynamical Systems

Academic Program: Applied Mathematics and Computer Science

The student will work on machine learning techniques applied to the study of dynamical systems. Specifically, the student will use different Neural Network architectures to approximate the equations governing a given system's evolution. This evolution may be intrinsically random, or we may add randomness to contemplate the possibility of approximating a large dimensional system by a low dimensional one. He will also test this methodology in several applications and report his results to get familiar with the problem and its input data.

4000000024

erik.vonschwerin@kaust.edu.sa

Machine Learning, Deep Neural Networks, Dynamical Systems, Numerical Analysis, Stochastic Numerics

Computational and Applied Mathematics

As the main project deliverable, we expect a scientific report describing the methodology developed in the internship and its numerical use in various applications. The working environment the student will use should include a GIT repository for all project-related materials to facilitate proper verification and feedback processes. These materials include, among others, the codes and the saved input-outputs corresponding to all tested cases

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Learning to Cooperate in Multi-Robot Systems

Academic Program: Electrical Engineering

How can we make a group of robots to cooperate in perception and manipulation to perform a variety of missions? Examples include a team of small robot helicopters and ground robots, equipped with manipulators (robotic arms), productively monitoring and harvesting crops in precision agriculture or proactively identifying and removing potential hazards in smart infrastructure applications. To realize this, the robots need to have the ability to organize as a team and to cooperate with their peers in team missions. The project aims at studying principles and algorithms to realize robots' ability to learn to cooperate. In particular, the main theme of the study focuses on how to generalize the robots' learning capability across diverse environments and even different application domains. To answer this question, we begin by studying reinforcement learning principles designed for multi-robot cooperation and systematically investigate how the robots' learning process depends on parameters defining the systems and environments. Then we develop new models and computational tools to train a team of robots that provide performance guarantees across a wide range of application scenarios.

BAS/1/1695-01-01

shinkyu.park@kaust.edu.sa

Robotics, Multi-Robot Learning, Multi-Robot Cooperation

Electrical and Computer Engineering

The goal of this project is to develop, implement, and test a multi-robot learning framework. The students will have opportunities to learn many of computational methods designed for multi-robot cooperation/learning and experience designing and implementing their own algorithms using multi-robot systems. The students are encouraged to work on research-oriented problems and expected to come up with their own creative solutions. They should have backgrounds in reinforcement learning and know fundamentals in multi-robot control/planning, and they are expected have experience with robotics software and proficiency in programming languages (C/C++ and Python).

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Developing bioinformatic tools for Multi-omic data integration

Academic Program: BioScience

The past two decades have provided unprecedented growth in data modalities and data availability within the biomedical research. As a result, methodologies for the multi-omic analysis of bulk (average profiles derived from hundreds to millions of cells), single-cell data or both are in continuous development. Our team has been involved in such developments working on multi-omic frameworks (STATegra framework + STATEgRa Bioconductor package), multi-omic DeepLearning based analysis (LIBRA - BioarXiv) and specific tools such as GeneSetCluster to summarize information derived from gene-set enrichment analysis. We are looking for highly motivated and skilled visiting students to work on one or several of the following challenges sub-projects: - Upgrading STATegRA Bioconductor package to account for the novel developments, including the single-cell analysis applications and the integration with GeneSetCluster analysis tool. - Novel Deep Learning-based methodologies for multi-omic analysis. - Implementing Cell-to-cell interaction analysis as part of a multi-omic integrative framework. We have existing proprietary data to work in the context of the Bone Marrow. For any selected student, the project to be conducted will be decided based on the student's interest, technical proficiency, and level of study. We expect for any participant (a) to bring motivation, enthusiasm, creativity, and hard work, (b) give lab seminars on your work, (c) collaborate with other lab members, and (d) produce a final written report. References of interest: - STATegra framework: https://www.frontiersin.org/articles/10.3389/fgene.2021.620453/abstract - STATegRa package: https://www.bioconductor.org/packages/release/bioc/html/STATegRa.html - LIBRA single-cell multi-omic framework: https://www.biorxiv.org/content/10.1101/2021.01.27.428400v1 Link to recent publications of the team: http://www.lunacab.org/publications/

BAS/1/1093-01-01

David.gomezcabrero@kaust.edu.sa

Single-cell analysis, multi-omic analysis, Deep Learning,

Biosciences, bioinformatics

Enhancing critical thinking, presentations skills, and scientific writing. The research, in collaboration and with support of team members, may lead to scientific publications. Obtaining a hands-on perspective at the frontier of bioinformatics, multi-omic analysis, and its applications in an interdisciplinary research group and environment.

BioScience

Biological and Environmental Sciences and Engineering

Undergraduate

Bringing Chromatin Conformation and Spatial profiling into clinical research

Academic Program: BioScience

The past two decades have provided unprecedented growth in data modalities and data availability within the biomedical research. As a result, methodologies for the multi-omic analysis of bulk (average profiles derived from hundreds to millions of cells), single-cell data or both are in continuous development. Our team has been involved in such developments working on multi-omic frameworks (STATegra framework + STATEgRa Bioconductor package), multi-omic DeepLearning based analysis (LIBRA - BioarXiv) and specific tools such as GeneSetCluster. As a next step, we aim to integrate into current integrative pipelines additional data-types such as Chromatin Conformation and Spatial profiling. We are looking for highly motivated and skilled visiting students to work on one or several of the following challenges sub-projects: - Integrating Chromatin Conformation information (such as HiC) in clinical oriented research. Myeloma as a case study. Proprietary data is available for such integration. - Integrating Spatial Transcriptomics and Cell-to-cell interaction analysis as part of a multi-omic integrative framework. We have existing proprietary data to work in the context of the Bone Marrow. For any selected student, the project to be conducted will be decided based on the student's interest, technical proficiency, and level of study. We expect for any participant (a) to bring motivation, enthusiasm, creativity, and hard work, (b) give lab seminars on your work, (c) collaborate with other lab members, and (d) produce a final written report. The project relies on multi-skilled collaborations involving biologists, clinicians, bioinformaticians and computational biologists. References of interest: - STATegra framework: https://www.frontiersin.org/articles/10.3389/fgene.2021.620453/abstract - STATegRa package: https://www.bioconductor.org/packages/release/bioc/html/STATegRa.html - LIBRA single-cell multi-omic framework: https://www.biorxiv.org/content/10.1101/2021.01.27.428400v1 - 3D data: https://www.nature.com/articles/s41467-020-20849-y

BAS/1/1093-01-01

David.gomezcabrero@kaust.edu.sa

Single-cell analysis, Multi-omic analysis, Deep Learning, Chromatin Conformation, Spatial Transcriptomics, Translational research

Biomedicine

Enhancing critical thinking, presentations skills, and scientific writing. The research, in collaboration and with support of team members, may lead to scientific publications. Obtaining a hands-on perspective at the frontier of bioinformatics, multi-omic analysis, and its applications in an interdisciplinary research group and environment.

BioScience

Biological and Environmental Sciences and Engineering

Undergraduate

Characterization of chemical contaminants in wastewater to predict its role on natural transformation among microorganisms

Academic Program: Environmental Science and Engineering

One of the principal barriers towards safe water reuse is an effective wastewater treatment process. Most countries treat wastewater through a series of physical, biological and chemical processes, including a final disinfection step, to decrease the bacterial counts to permissible levels. The inactivation of pathogens is particularly important to protect public health and the environment. However, the use of chemical-based disinfectants can result in a wide diversity of disinfection byproducts (DBPs) which in turn alter the toxicological characteristics of treated wastewaters. In addition, wastewater contains a wide range of chemical contaminants that can also impose potential mutagenic effect on microorganisms. Our group has previously provided demonstrations on how disinfection byproducts (DBPs) can trigger mutagenicity and natural transformation events (which is the translocation and integration of foreign DNA that then allow the microorganisms to gain new functional traits). This project aims to perform an in-silico assessment on whether the other chemical contaminants present in wastewater would also play a role in natural transformation events.

BAS/1/1033-01-01

peiying.hong@kaust.edu.sa

Mutagenicity, reactive oxygen species, natural transformation, extracellular DNA

Environmental Science/Chemistry

A database on the features associated with chemical contaminants and their roles in natural transformation or other modes of horizontal gene transfer

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Undergraduate

Water Desalination and Reuse Center

Robot Navigation in Crowded Environments

Academic Program: Electrical Engineering

One of big challenges in robotics research is in enabling robot navigation in crowded environments. As one key technical difficulty, in such environment, a robot would trap into a deadlock state where the robot is unable to advance to its destination, especially when it is surrounded by pedestrians and perceives them as obstacles which the robot is programmed to avoid collision against. This problem is widely known as a "freezing robot problem" and acts as a major hurdle in deploying robotic systems in real-world applications. We study this problem in the context of human-robot interaction and develop new algorithms that ensure deadlock-free robot navigation in pedestrian-populated environments. The project aims at developing both principles and algorithms to address the freezing robot problem: we begin by investigating how the human-robot interaction can be understood as a feedback interconnection of human and robot decision-making models and then identify under what specifications on the robot's decision-making model, the robot is guaranteed to be deadlock-free. We will explore tools from feedback control theory and game theory to find such specifications and develop robot navigation algorithms satisfying them. Ultimately, we will carrying out experiments using multiple mobile robot platforms to validate our framework in pedestrian-populated areas.

BAS/1/1695-01-01

shinkyu.park@kaust.edu.sa

Robotics, Human-Robot Interaction, Feedback Control

Electrical and Computer Engineering

The goal of this project is to develop, implement, and test a deadlock-free robot navigation framework based on well-established multi-agent decision-making models. The students will get to learn many of tools designed for robot perception and navigation tasks and gain experience in designing and implementing their own algorithms into robot platforms. Then the students are expected to design new methods to predict pedestrian motions using data from on-board sensors and to maneuver the robot in crowded areas. The students are encouraged to work on research-oriented problems and expected to come up with their own creative solutions. They should have backgrounds in robot perception and motion planning, and they are expected have experience with robotics software and proficiency in programming languages (C/C++ and Python).

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Numerical approximation of partial differential equations

Academic Program: Applied Mathematics and Computer Science

The numerical approximation of partial differential equations is a relevant field of applied mathematics. Several projects are available at my research group, ranging from purely theoretical studied to more applied and computational tasks. Theoretical project will involve the study and analysis of the properties of the approximation of some partial differential equations. Computational projects are related to the implementation and testing of research codes for scientific computing. The areas of applications include electromagnetism, structural mechanics, fluid-dynamics, fluid-structure interactions.

BAS/1/1688-01-01

daniele.boffi@kasut.edu.sa

Numerical Analysis, Applied Mathematics, Scientific Computing

Numerical analysis, Applied Mathematics, Scientific Computing

Implementation and testing of the proposed algorithms. Study and analysis of the properties of approximating schemes for partial differential equations.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Imaging with a Drone-borne Synthetic Aperture Radar

Academic Program: Electrical Engineering

Due to their mobility, cost-effectiveness and availability, small-scale drones (or unmanned aerial vehicles (UAVs)) are increasingly being used as a platform of choice for sensing or imaging critical target areas/objects in numerous applications. In contrast to optical sensors, radars provide all-weather sensing capabilities. However, radars are limited in the resolution of the images that they generate. One way to circumvent this limitation is to use a synthetic aperture radar (SAR), which can be realized by collecting radar measurements over a pre-defined path. This can be easily achieved via a maneuverable platform such as the drones. Thus, drone-borne radars can provide a robust and flexible solution to the sensing problems. In this project, we model and test drone-borne SAR in order to enhance the resolution of radar images. The project involves simulations as well as (possible) practical experiments.

BAS/1/1665-01-01

shahzad.gishkori@kaust.edu.sa

Drones, UAVs, Radars, Imaging

Electrical Engineering

1) Simulating synthetic aperture radar via Matlab coding, 2) Designing the experimental setup and taking practical measurements, 3) Generating processed radar images, 4) Documenting the project and its outcomes

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Causal and Fair Machine Learning

Academic Program: Computer Science

The exact topic depends on the student's interest, student's background, and previous research experience. Generally speaking, there are mainly three topics of this project: 1. Designing Fair Machine Learning Algorithms. In this project, students will focus on how to make the current machine learning algorithms be fair. They will also explore the fairness issue of the current machine learning algorithms, especially for healthcare data. 2. Causality as a tool for de-biasing current deep learning algorithms. Students will use the idea of causality to different deep learning tasks to de-bias the datasets or algorithms in order to improve the accuracy and trustworthiness. 3. Causality as a tool for invariant learning. This project mainly focuses on transfer learning, students will use causality to design transfer learning algorithms.

BAS/1/1689-01-01

di.wang@kaust.edu.sa

Machine Learning, Deep Learning

Causal Inference, Fairness, Transfer Learning, Deep Learning

During the project, students will have opportunity to learn about some topics in trustworthy machine learning, especially fair learning, transfer learning and causal learning. They will learn and implement the SOTA methods. Hopefully, they may produce some publication after the intern.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Robust/Differentially Private Machine Learning

Academic Program: Applied Mathematics and Computer Science

The topic is flexible and depends on student's background, mathematical knowledge, previous research experience. Generally, this project mainly focuses on how to design robust (especially robust against to outliers or heavy-tailed distributions) or private (or forgettable) algorithms for some foundamental problems in machine learning, deep learning or statistics. Students will provide theoretical guarantees via using mathematical tools from probability, learning theory, optimization and high dimensional statistics. Also, student will analyze utility-privacy tradeoff or robustness-utility tradeoff.

BAS/1/1689-01-01

di.wang@kaust.edu.sa

Machine Learning, Privacy, Statistics

Machine Learning, Data Privacy, High Dimensional Statistics

Students will learn some fundamental techniques and results in learning theory, high dimensional statistics, optimization and differential privacy. They will also implement machine learning or statistics algorithms via using Matlab or Python. Hopefully they could have publications after the project.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Foundations of Private and Fair Statistics

Academic Program: Statistics

The topic is flexible and depends on student's background, previous experience and mathematical skill. Specifically, in the topic, students will explore basic statistical model or problems for different types of data in the differential privacy or fairness model. For statistical model , topics include component analysis, supervised learning, mixture model , et al. For data, topics include survival data, functional data, network analysis. Students will design new algorithms to solve these problems and provide theoretical guarantees on the utility-privacy or utility-fairness tradeoff. Moreover, they will implement these algorithms on some sensitive data such as healthcare and biomedical data.

BAS/1/1689-01-01

di.wang@kaust.edu.sa

Machine Learning, Statistics, Privacy

Machine Learning, Data Privacy, Statistics

Students will learn basic techniques and terminologies in differential privacy, fairness and some topics in statistics. They will have the chance to implement the best-known algorithm for some specific problems. Hopefully, they could have some new results and publications after the project.

Statistics

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Lithofacies classification with transition-aware Neural Networks

Academic Program: Environmental Science and Engineering

In the last couple of years, the use of Machine Learning has emerged in various areas of geoscience with the promise to automate the solution of otherwise manually intensive tasks or improve upon currently used algorithms. Lithofacies classification from well logs and seismic pre-stack data represents one of the earliest and most successful its use cases to date. Both tree- and neural network-based supervised learning methods are nowadays used to classify hundreds of well logs or entire seismic data in a matter of hours. Whilst providing high accuracy, most approaches currently ignore the fact that some classes cannot occur above others (e.g., oil is always found below gas) and, more in general, fail to produce consistent transition probabilities between the training data and predicted labels. In this project we will investigate a strategy for enforcing our prior knowledge about facies transitions through an ad-hoc extension of the cost function of NN-based classifiers. This will be followed by a thorough comparison with other state-of-the-art classifiers on synthetic and field data.

BAS/1/1414-01-01

Matteo Ravasi

Geoscience, Machine Learning, Statistics

Geoscience

The candidate will be tasked with: - Creating a synthetic dataset using basic principles of rock physics, fluid substitution and seismic modelling. - Develop and implement a novel, transition-aware NN-classifier and compare its performance with other state-of-the-art classifiers - Apply the newly developed method to a field benchmark well-log dataset (e.g., from SEG ML contest) and a field pre-stack seismic dataset (e.g., Volve data)

Environmental Science and Engineering

Physical Sciences and Engineering

Undergraduate

Hydrodynamic characterization of membrane spacers

Academic Program: Environmental Science and Engineering

Membrane spacers are important for the energy consumption, rejection of unwanted components and robustness towards membrane fouling. The mass transfer rate and friction losses in a spacer filled channel are usually expressed as generalized semi-empirical relations.  The objective of this project is to experimentally establish these semi-empirical relations for several available membrane spacers, and to correlate these relations with dimensions of the spacers.

BAS/1/1024-01-01

Graciela Gil

Membrane filtration, biofouling, mass transport, hydro dynamics

​Chemical & Biological Engineering

The student should deliver a set of semi-empirical mass transfer and friction relations, analyze the effect of spacer geometry on these relations, and critically evaluate the currently used generalized relations.

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Undergraduate

Water Desalination and Reuse Center

Protocol development for biomass quantification in membrane autopsies

Academic Program: Environmental Science and Engineering

A membrane autopsy is a valuable tool used in membrane (bio)fouling studies. One of the objectives of the autopsy is to quantify the amount of biomass. The current method involves sonication of the sample, followed by filtration and DOC measurement. The objective of the project is to investigate the influence of the sample preparation method on the measured value. 

BAS/1/1024-01-01

Graciela Gonzalez Gil

Membrane filtration, biofouling, chemical analysis

Chemical & Biological engineering

The student should critically evaluate the current method, and propose or develop improvements/alternatives.

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Undergraduate

Water Desalination and Reuse Center

KAUST-BioMOFs

Academic Program: Chemical Science

This project entitles the design and synthesis of biodegradable and biocompatible metal organic frameworks for protein encapsulation and delivery

BAS/1/1343-01-01

Niveen M. Khashab

encapsulation, delivery, nanotechnology, organic chemistry, smart materials

Supramolecular Chemistry/Nanotechnology

- prepare MOFs with calcium and magnesium 

- fully characterize the obtained MOfs

Chemical Science

Biological and Environmental Sciences and Engineering

Undergraduate

Advanced Membranes and Porous Materials Center

Impact of Holocene climatic shifts on the spatial sediment distribution in a carbonate lagoon

Academic Program: Energy Resources and Petroleum Engineering

The objective of this internship is to collect and analyze soft sediment cores from the Al Wajh carbonate lagoon in the Red Sea. The intern will help acquire the cores, conduct standard analyses of grain size and mineralogy, perform component and facies analyses, and prepare samples for isotope analysis.

BAS/1/1400-01-01

Marwa Ghammam marwa.ghammam@kaust.edu.sa

Carbonate sedimentology, Paleoclimate, Paleoceanography

Geology

This study will provide new insights on the relationships between short-term climatic variations and spatial facies variability observed in mixed clastic/carbonate lagoon sediments. It will also contribute to an improved understanding of lateral heterogeneities in carbonate reservoirs that formed in reef environments.

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Undergraduate

Influence of short-term climate changes on the spatial facies distribution ina carbonate platform lagoon during Holocene (N Red Sea)

Academic Program: Earth Science and Engineering

During the Early Holocene (9.5 to 6.5 ka), climate in the N Red Sea changed from arid to humid conditions and resulted in increased precipitation in the N Red Sea area. As a consequence, carbonate shelfs along the Red Sea margins suffered increased river-discharge including a high influx of siliciclastic sediments and nutrients. This prominent short-term climate change is, so far, only studied in deep-sea sediments, while the impact on the shallow-water carbonate realm is poorly investigated. In order to fill this gap, the objective of this project is to analyse four soft sediment cores collected from a carbonate platform lagoon in the N Red Sea (Al Wajh platform). Besides sedimentological standard analyses (e.g. grain size, mineralogy), the applicant will perform component and facies analyses and will prepare samples for isotope measurements as well as dating. Outcome of this study will provide new insides in the relationship between short-term climate variations and spatial facies variability. Besides the fundamental understanding of sedimentological processes, the results will also help to improve the understanding of the formation of lateral heterogeneities in carbonate reservoirs. It is expected that the applicant will take part in multi-day research cruises and field trips.

BAS/1/1399-01-01

Alexander Petrovic

Carbonate Sedimentology, Climate Change, Marine Geology

Carbonate sedimentology, Paleoclimate, Paleoceanography

- Detailed analyses of four sediment cores

- Development of a core stratigraphy 

- Correlation of all four cores

- Development of a Palaeo-reconstruction and a depositional model

Earth Science and Engineering

Physical Sciences and Engineering

Undergraduate

Ali I. Al-Naimi Petroleum Engineering Research Center

Numerical Study of CO2 Storage in a Deep Aquifer in Saudi Arabia

Academic Program: Energy Resources and Petroleum Engineering

The ongoing greenhouse gas emissions to the atmosphere is a global concern. Climate change could be mitigated by stabilizing and reducing the levels of heat-trapping greenhouse gases in the atmosphere. In this context, the role of Carbon Capture and Storage (CCS) becomes important, as it is one of very few options available to us to maintain the value of fossil fuels whilst reducing emissions. CCS technology corresponds to a mature and feasible solution that can be applied to meet the objectives set by various governments and agreements worldwide for reducing greenhouse gas emissions from carbon intensive industries. CCS is an essential component in all IPCC scenarios that limit global warming, and has also been recognized as a main enabler for Circular Carbon Economy (CCE). The objective of this project is study the feasibly of CO2 storage in a deep aquifer in Saudi Arabia. The focus will be on building a 3D high-resolution geological model in Petrel. The model will incorporate well data, outcrops, and analogs. Different realizations will be considered to account for uncertainties. Simulations will then be conducted to assess the storage capacity, development alternatives, what-if scenarios, and risk assessments.

BAS/01/1390-01-01

Hussein Hoteit

CO2 sequestration 3D geological model Peservoir simulation Petrel

Geology and Reservoir Engineering

- Build 3D geological model in Petel - Generate high-resolution corner-point simulation grids - Populate the static model - Propose alternative development plans - Perform simulations using Intersect - Document findings in presentations and a final technical report

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Undergraduate

Ali I. Al-Naimi Petroleum Engineering Research Center

Tectonic evolution through analogue modelling

Academic Program: Energy Resources and Petroleum Engineering

The Arabian plate geology group is building a state of the art analogue modelling laboratory, which will be functional by year-end 2020. The apparatus consists of two rigid plates which can be displaced in x,y and z directions. This setup brings unlimited variety for future geological models. The analogue modelling apparatus can be used with either CT-scanner or normal laboratory conditions, for which an additional acquisition apparatus is under construction. This equipment will be used primarily for modeling large-scale tectonic processes of the Red Sea and the Dead Sea Transform.

BAS/1/1400-01-01

Jakub Fedorik (jakub.fedorik@kaust.edu.sa)

Structural geology, Analogue modelling, Arabian plate geology

Structural geology

Finalizing of construction of the photogrammetry apparatus, designing the analogue model setup, running experiments, analysis of data, PIV or structural interpretation and comparison to natural cases. 

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Undergraduate

Ali I. Al-Naimi Petroleum Engineering Research Center

Large-eddy Simulation of boundary layer bypass transition

Academic Program: BioScience

Large-eddy simulation is a viable approach to investigate high Reynolds number wall-bounded turbulent flows. In this project we will simulate bypass transition of the boundary layer on a flat plate. The additional details are in the pdf file attached. 

BAS/1/1349-01-01

Dr. Wan Cheng

Large-eddy simulation Computational fluid dynamics Boundary layer flows Turbulence

Computational fluid dynamics

Transition of incompressible boundary layer flow requires perturbations with specific features.Perturbation could come from wall, or out of the boundary layer. Study of incompressible transition mainly employ either DNS or LES

 

BioScience

Biological and Environmental Sciences and Engineering

Undergraduate

Advanced Membranes and Porous Materials Center

High-resolution numerical modeling of atmospheric processes over the Arabian Peninsula

Academic Program: Earth Science and Engineering

The study will focus on the simulation of high-resolution regional atmospheric processes at the Arabian Coast of the Red Sea. This area is one of the most populated in Saudi Arabia, and it is planned to be intensively developed in the scope of the 2030 vision. The project will involve modeling using the Weather Research and Forecast model WRF to evaluate the effect of urbanization over the coastal plain. The simulation will be conducted on the KAUST supercomputer system and will be focusing on the impact of the coastal urbanization on sea and land breezes. The analysis will require extensive data processing and "big-data" manipulation.

BAS/1/1309-01-01

Prof. Georgiy Stenchikov, Dr. Suleiman Mostamandi

Regional meteorological models, climate, atmospheric physics

Atmospheric physics, numerical modeling, climate and regional circulation

Data set with the results of model runs

Data analysis software

Data analysis results

Report on data set organization, analysis software, and interpretation of the results 

Earth Science and Engineering

Physical Sciences and Engineering

Undergraduate

Assessment of CCS in Saudi Arabia

Academic Program: Energy Resources and Petroleum Engineering

The aim of the project will be to contribute to the assessment of the CCUS potential in Saudi Arabia through the assessment of stationary CO2 emissions as well as the cost analysis (separation, capture, and transportation costs involved in CCS). The database for CO2 emissions from stationary sources in the Kingdom includes emissions from electricity generation, desalination, oil refineries, cement industry, petrochemicals, and iron & steel from 2016, that need to be verified and updated with most up-to-date data. The assessment will also include looking at identifying potential storage locations and estimating the capacity of storing CO2 in deep aquifers, depleted hydrocarbon reservoirs, and basaltic rocks. The VSRP student will be involved in data analysis and interpretation in Petrel and, by picking up new ideas and techniques, will be able contribute to the further development of the Petrel/ArcGIS geological model of Saudi Arabia in order to identify and characterize potential CO2 storage sites in the country. The student will also help in establishing and developing the national carbon storage atlas for KSA. A carbon storage atlas is a comprehensive assessment of all aspects of CCS including CO2 emissions, best practices, and emerging technologies related to carbon capture, transportation, and assessments of storage in potential geological sites and associated costs. The work may include this section petrography using optical and electron microscopes to characterize rocks for carbon disposal.

BAS/1/1400-01-01

Alexandros Tasianas eamail alexandros.tasianas@kaust.edu.sa

CO2 storage, CCS, GIS, geology

Carbon Capture Utilization and Storage (CCUS)

Contribute to the construction, verification and use of the 3D geological model of the Saudi Arabia using GIS and specialized geological interpretation software (creation/modification of formation top surfaces corresponding to potential storage sites, input of data e.g. well information, etc) Verification of input and update of the existing GHG emissions database with the most recent data for the current CO2 stationary sources with locations, rates and industry sector for the country.

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Undergraduate

Ali I. Al-Naimi Petroleum Engineering Research Center

Diversity and ecology of the coral genus Leptoseris in mesophotic environments

Academic Program: Marine Science

Coral-dominated benthic mesophotic communities are receiving increasing attention as new technologies allow their exploration and new molecular approaches are used to understand the evolution of the organisms that are part of them. They remain, however, largely unexplored and several aspects of their biological diversity and biogeography have not been addressed so far. Among the dominant taxa in benthic mesophotic assemblages, the scleractinian genus Leptoseris is particularly challenging in terms of our understanding of its diversity and ecology. We are looking for a graduate student to investigate: 1) an assessment of the morpho-molecular diversity of mesophotic Leptoseris in the Red Sea and the Indo-Pacific, 2) a preliminary characterization of the zooxanthellae communities associated to mesophotic Leptoseris.

BAS11090-01-01

​​Coral reef biodiversity

Marine Science

Biological and Environmental Sciences and Engineering

Diversity and biogeography of the organ pipe coral Tubipora

Academic Program: Marine Science

In the tropical marine environment, coral-dominated benthic communities are characterized by a high biological diversity. In coral reef communities, different taxa of benthic marine invertebrates play a key role in structuring the environment and providing habitat for other organisms. Several reef building cnidarians are in symbiosis with the photosynthetic Symbiodinaceae, or zooxanthellae. Among those, the zooxanthellate octocoral genus Tubipora is a common, locally abundant and yet poorly known component in the Red Sea and the Indo-Pacific coral communities. Easily recognized underwater and in the fossil record, despite a remarkable morphological variation of the living animal, the genus is currently considered monospecific. However, preliminary molecular phylogenies have shown that several morpho-molecular species might actually exist. Moreover, the diversity of the invertebrate fauna associated with Tubipora, and hence its role as a biodiversity aggregator, remains unexplored. We are looking for a graduate student to: 1) investigate the morpho-molecular diversity of Tubipora in the Red Sea and the Indo-Pacific, 2) provide a preliminary characterization of the zooxanthellae communities and invertebrate fauna associated to Tubipora in the Red Sea.

BAS11090-01-01

​​Coral reef biodiversity

Marine Science

Biological and Environmental Sciences and Engineering

Body Area Networks

Academic Program: Electrical Engineering

Students will be engaged in design, simulation and evaluation of a body area network using on-skin communication modules. Accurate, real time sensing of body vital functions leads to better preventative medicine approached and more accurate diagnosis. State of the art wireless solutions, such as Bluetooth, attempt to provide such functionality, however their relatively large size and power demands limited their widespread use for personal telemetry. This project advocates the use of a new communication channel instead of air, which is the “human body” itself. Our vision is to provide a network of smart mini-distributed body mounted sensors that can perform personal telemetry and connect to the external world wirelessly using a central hub. The sensors themselves do require a radio frequency section or antennas since they directly interface to the skin (similar to smart watches) and hence will have a significantly reduced area, and use at least an order of magnitude less power, enabling a variety of network architectures and applications. The system will use very low power pulses for communication, well below what is required by health guidelines and exposure limitations. Distributing such small and smart sensors over the human body will allow users to monitor many vital signals, such as body temperature and electrocardiogram with unprecedented accuracy.

BAS/1/1686-01-01

Electrical Engineering ​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Conceptual design of membrane processes

Academic Program: Chemical and Biological Engineering

The aim of this project is to simulate different membrane processes to develop rules of thumb for conceptual design of membrane processes. The student in this project will learn how to use the software Aspen Plus®, a wide used software in petrochemical industry, to simulate the membrane process for the separation of propylene and propane. Through this project, the student will learn all the basic knowledge of membrane processes, understand the reason why gas separation is so important in chemical industry and what are the advantages and challenges in the membrane studies. The education aim of the project is to stimulate the interest of the student in membrane studies.

BAS/1/1375-01-01

test@gmail.com

x

​Chemical Engineering

Please contact professor for details.

Chemical and Biological Engineering

Physical Sciences and Engineering

Graduate

Advanced Membranes and Porous Materials Center

Data and power conversion using Microelectromechanical systems (MEMS)

Academic Program: Electrical Engineering

In this project, the interns will work with senior PhD students on a new circuit design paradigm for ultra low power IoT and biomedical applications. This new design approach is based on MEMS and NEMS, which can offer superior switching properties, in terms of energy consumption, compared to the mainstream CMOS technology. As such, these micro/nanoswitches are ideal for digital and interface circuit design applications, as well as on-chip energy conversion. This project includes a range of theoretical and experimental topics, from modelling these novel devices, to simulation of simple and complex circuits, and finally, system integration and hybrid CMOS-MEMS fabrication and characterization.

BAS/1/1660-01-01

​Electrical Engineering, Microelectronics, MEMS

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Spintronics Memory, Logic Devices and Circuits for Neuromorphic Computing Systems

Academic Program: Electrical Engineering

In this project, the interns will work with senior PhD students and one postdoc on developing a platform for the emerging field of neuromorphic (aka brain-inspired) computing, based on beyond-CMOS devices, namely spintronics memory cells and logic gates. This project tries to address the well-known problems of the dominant CMOS technology, such as increased leakage, power density and reaching the limits of scaling. The project includes modelling, simulation, fabrication, characterization and system integration, and the intern(s) will have the opportunity to get involved in some or all stages of the work.

BAS/1/1660-01-01

​​Electrical Engineering, Microelectronics, Spintronics

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Molecular doping of organic semiconductors for high efficiency optoelectronic devices

Academic Program: Materials Science & Engineering

Doping of organic semiconductors plays a fundamental role to overcome typical limitations observed in organic electronic devices. Organic light-emitting diodes (OLEDs) and organic solar cells (OSC) benefits for instance of the introduction of highly conducting injection layers, while high conductivity is one of the basic requirements for organic thermoelectric materials. Organic field-effect transistors (OFETs), on the other hand, are almost entirely based on intrinsic materials and doping has been mainly employed to pattern areas close to the contacts in order to improve charge injection.1 Beside the investigation of high degree of doping, ultralow doping has been recently attracting great interest, with the aim of directly dope the devices active layer that were usually based on intrinsic organic semiconductors. OSC containing small weight percentage of molecular dopants in the bulk heterojunction were found to display an increased short-circuit current (Jsc) and hence higher power conversion efficiency (PCE), when compared to their intrinsic counterpart.2 OLEDs have been reported with improved performance and device color modulation with dopant concentration was reported.3 A similar approach has been employed for OFETs, where extremely high mobilities, beyond the highest reported in literature, have been reported for organic semiconductors blended with low concentrations of dopants.4–6 These latter approaches are based on the addition of low fractions of dopants (£ 1-2 mol%), hence providing a different scenario from that of highly doped conducting layers. Strong efforts have been spent in the understanding of doping in organic semiconductors, both from a chemical and physical point of view, providing hence guidelines for the synthesis and application of more effective dopants. Recently, Lewis acid have been reported to show promising features as dopants for solution-processed polymers and small molecules.4 Here we propose a systematic study of different types of Lewis acids to investigate the potentiality of this doping strategy for organic field-effect transistors. Different processing routes and compositions will be studied in order to establish relevant structure/processing/property interrelationships.

BAS/1/1389-01-01

​​Materials science

​1. Prepare solutions and learn coating methods for the formation of solution processable thin films. [Month 1-6] 2. Learn how to prepare and measure organic electronic devices, such as high emitting diodes, organic solar cells and field-effect transistor. [Month 3] 3. Study the influence of dopants in structural and optical properties of organic semiconductors and devices. [Month 4] 4. Prepare project updates reports and presentation. [Month 6]​ 

Materials Science & Engineering

Physical Sciences and Engineering

KAUST Solar Center

Statistical models based on stochastic partial differential equations

Academic Program: Statistics

The student will learn about modern statistical methods based on stochastic partial differential equations (SPDEs). One important advantage with formulating statistical models using SPDEs is that it facilitates non-Gaussian extensions of several popular Gaussian models. Such extensions are useful for applications where the data has features that cannot be captured by Gaussian models. The goal of the project is to implement and compare these models for applications to longitudinal medical data and spatial environmental data.

BAS/1/1687-01-01

​Statistics

​​Written report and computer code that reproduces the results

Statistics

Computer, Electrical and Mathematical Sciences and Engineering

Biodiversity of Red Sea Reef Fishes

Academic Program: Marine Science

Documenting reef fish communities through surveys and collections across spatial and temporal scales is key to understanding changes of biodiversity across natural environmental gradients and local habitats, or to predict future trajectories in response to local and global stressors. Using a range of sampling and survey methods, we are building a comprehensive picture of fish communities within the Red Sea. Work will focus on the documenting fish communities in reef and non-reef habitats (e.g., mangrove, seagrass, macroalgae) to understand the connection and importance of habitats to ecosystem function and services. This focuses on conspicuous and cryptic fishes with opportunities to conduct field (diving, fish surveys and collections) and lab work (dissections, genetic barcoding).

BAS/1/1010-01-01

​​Biodiversity, Ecology, Marine Science

​Depending on the results, the student researcher may also contribute to a scientific publication detailing the work and findings​.

Marine Science

Biological and Environmental Sciences and Engineering

Red Sea Research Center

Connectivity of Shark Populations

Academic Program: Marine Science

​Ongoing research conducted by the Reef Ecology Lab and its collaborators have generated a diverse collection of shark and ray genetic samples. Analysis of these samples could provide insight into both elasmobranch biogeography and population ecology. Specific projects include investigating broad population genetics of hammerhead sharks in the Red Sea and Arabian Gulf or looking at fine-scale differences between reef shark sub-populations within the Red Sea. Undergraduate research will mostly focus on lab work, performing DNA extractions, running PCRs, and analyzing our existing collection of genetic samples. There may also be opportunities for fieldwork, including fish market surveys and catch-and-release sampling trips.​

BAS/1/1010-01-01

​Population Genetics

​Depending on the results, the student researcher may also contribute to a scientific publication detailing the work and findings. 

Marine Science

Biological and Environmental Sciences and Engineering

Red Sea Research Center

Lactate signaling in synaptic plasticity

Academic Program: BioScience

Our lab is interested in understanding the signaling and metabolic interplay taking place between neurons and supporting glial cells during normal brain functions and in neurodegeneration. Neurons expend a considerable amount of energy on neurotransmission while glia cells provide neurons with metabolic substrates, antioxidants and trophic factors. In addition to its role as an astrocyte-derived metabolite fueling the needs of active neurons, lactate has recently emerged as a signaling molecule in the brain..​​

BAS/1/1030-01-01

​Neurobiology, Cell Biology

​The student will learn to prepare, transfect and maintain HEK293 cells and primary cultures of neurons. She or he will also develop PLAs and use fluorescent microscopy to study the signaling role of lactate in the potentiation of NMDA receptors in neurons and in HEK293 cells expressing wild-type and/or mutant CaMKII/NMDA receptors​

BioScience

Biological and Environmental Sciences and Engineering

Unraveling fungi community patterns in Red Sea coral reefs

Academic Program: Marine Science

It is widely known that coral reefs represent one of the most biodiverse ecosystems on Earth. There have been numerous attempts to quantify and evaluate species richness and functional diversity in reef environments. However, the majority of research so far has focused on macro organisms - most likely due to difficulties in evaluating the hidden “cryptobiome” of reefs in a standardized way. The deployment of Autonomous Reed Monitoring Structures (ARMS), in combination with metabarcoding, successfully performed by KAUST scientists in the recent past can be key to identify taxonomic and functional groups of Red Sea coral reefs associated organisms. Studies using ARMS in the Red Sea so far have targeted eukaryotic and bacterial taxa. However, fungal communities that can play critical roles in reef functioning have been overlooked. To close the knowledge gap on fungal communities in Red Sea coral reefs, we are looking for a student (undergraduate or graduate) to investigate the following aspects: (1) Evaluation of fungal community compositions and their spatio-temporal distribution throughout Red Sea ARMS deployment sites, based on metabarcoding data analysis. Which gradients do emerge and how do they relate to environmental variables, such as sea surface temperature?; and (2) How are fungal communities connected to bacterial communities identified by Pearman et al. (2019)?

BAS/1/1065-01-01

​Coral reef biodiversity and functioning

​The overall aim of the project is a peer-reviewed publication with the student being the first author​

Marine Science

Biological and Environmental Sciences and Engineering

The effect of rootstock-scion combination on microbiome selection by fruit plants

Academic Program: BioScience

Grafting is a common agronomic practice performed on different fruit plants such as, among others, apple tree, other Rosaceae and grapevine. It is used for improving the fruit cultivar adaptation to specific soil and for controlling some plant parasites. The rootstock affects scion development by influencing the reproductive performance, vigor, biomass accumulation and distribution in the plant, phenology and fruit yield. Moreover, a recent publication highlighted that rootstock type influences the recruitment by plants of microorganisms from the soil, which can be defined as the ‘seed-bank’ for root microbiome assemblages (Marasco et al., 2018, Microbiome 6:3. Doi 10.1186/s40168-017-0391-2). An aspect that is still overlooked is if and how the rootstock-scion combination affect the recruitment of the microbiome and their migration and colonization of the tissues in different plant compartments and organs. A deeper knowledge on this aspect is pivotal to better understand the factors steering the recruitment and the flux of microorganisms from the soil through the roots and within the plant compartments. Moreover, it would be interesting to unravel which rootstock-scion combinations can primarily influence the fruit quality, by inferring the functional diversity of the selected microbiome starting from high-throughput Illumina 16S rRNA gene sequencing. To investigate the community structure of the endophytic microbiome in different plant compartments (e.g. root, shoot, leaf, fruit) comparing several combinations of rootstock-scion pairs. The research will be conducted on fruit trees, e.g. grapevine, and the bulk soil (i.e. the soil not affected by root exudates) will be used as the reference microbial ‘seed-bank’. ​​

BAS/1/1065‐01‐01

​Plant-microbe interactions

-​Creation of 16S rRNA gene libraries from soil and plant metagenomes for the description of the structure and taxonomy of the bacterial community associated to different plant compartments and to the bulk soil - Quali/quantitative identification of the bacterial taxa present in 16S rRNA libraries - Study of the alpha- and beta-diversity of the microbiome in different plant compartments according to the rootstock-scion combinations. 

BioScience

Biological and Environmental Sciences and Engineering

CRISPR-based genetic engineering of stem cells for in vitro production of human blood

Academic Program: BioScience

Blood is the most commonly transplanted tissue in the clinic. The demand for blood transfusion has outstripped the donation-based supply worldwide. It is highly desirable to develop a technology to produce functional human blood cells in vitro. Such technology could greatly expand the general blood supply as well as provide novel therapeutics to patients. Human induced pluripotent stem cells (hiPSC) are an ideal starting population for in vitro production of blood because of their tremendous capacity to proliferate and to differentiate into all types of blood cells. We are seeking highly motivated students to apply CRISPR genome-editing technology to generate genetically modified hiPSC for efficient large-scale production of human blood. Candidates will have exposure to sophisticated technologies in stem cell biology such as FACS, hypoxia workstation, and bioreactor.​

BAS/1/1080-01-01

​molecular biology, cell biology, stem cell biology

​The candidate will learn the techniques of hiPSC culture. He or she will design and test CRISPR/CAS9 nucleases for generating desired genetic modifications at predetermined gene loci. The candidate is expected to validate successful modifications using molecular biology techniques. A pilot in vitro blood differentiation experiment will be carried out to test the differentiation potential of modified hiPSC lines.

BioScience

Biological and Environmental Sciences and Engineering

Multilevel and Unbiased Monte Carlo Methods for Option Pricing

Academic Program: Applied Mathematics and Computer Science

This project will focus on the numerical estimation of financial options. The latter are contracts associated to financial objects such as stocks, which can be mathematically expressed as expectations with respect to a diffusion process. In this project, we will develop Monte Carlo methods which can provide numerical estimates of these option prices, which are not available in closed forms. In particular, the diffusion processes will have to be time-discretized and we will use advanced multilevel and unbiased techniques to provide estimates sometimes with no time-discretization error.​

BAS/1/1681-01-01

​Computational and Numerical Methods

​Implementation and development of algorithms​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Online Outlier Detection for Functional Data

Academic Program: Statistics

The student will learn state-of-the-art statistical methods for functional data analysis and spatial statistics, explore various approaches of functional data ranking and outlier detection, especially for images and surfaces, develop algorithms for online outlier detection with applications to spatial deformation detection and brain signal analysis.​

WBS BAS/1/1655-01-01

​Statistics, Data Science, Environmental Science, Computer Science, Applied Mathematics

​At the end of the internship, the student is expected to implement the designed application and submit a written report or a poster​

Statistics

Computer, Electrical and Mathematical Sciences and Engineering

Internship on Deep learning Methods for Satellite Data Downscaling

Academic Program: Statistics

The student will learn state-of-the-art statistical and machine learning methods for image super-resolution, explore various sources of satelliteimages and deploy experiments to manipulate and analyze large scale dataset.​

WBS BAS/1/1655-01-01

​Statistics, Data Science, Environmental Science, Computer Science,Applied Mathematics​

Statistics

Computer, Electrical and Mathematical Sciences and Engineering

Imaging the interfacial charge carrier dynamics at axial p-n junction nanowires

Academic Program: Chemical Science

​To optimize the light harvesting, multiple junctions with different band gaps can be combined to match the solar spectrum, but lattice matching requirements severely limit the materials available for devices based on thin film growth. In general, nanowires (NWs) have emerged as building blocks for electronic and photonic technologies due to their distinct advantages over its bulk and planar counterparts. Multi-junction solar cells containing several p-n junctions which can be used to surpass the Shockley−Queisser efficiency limit in solar cells. However, the carrier dynamics at the interfaces of the p-n junctions are still not well understood. Being in this regime, the classical picture of photo-induced charge transfer at a heterojunction can be described as follows: right after excitation, electron-hole pairs are generated. This is followed either by electron-hole separation and drifting in opposite directions under the influence of the electric field of the p-n junction, or the electron-hole pairs can recombine radiatively by emitting a photon, or non-radiatively by carrier trapping or/and Auger recombination. However, where the exciton is localized and trapped, how the transfer occurs and how it depends upon the local environment is an important as yet unanswered question. The processes by which carriers transfer back across the interface and recombine, thereby returning to the equilibrium state, are highly dependent upon the local environment and are not fully understood and they cannot be catalogued using spectroscopic techniques. In other words, the accessibility of these dynamical processes by static imaging or steady-state and time-resolved spectroscopic techniques is very limited. The unique opportunity to visualize the carrier dynamics selectively on the material surface can only be accessed by 4D S-UEM with fs temporal and nm spatial resolutions. We will begin by utilizing the S-UEM technique to investigate charge dynamics in n-InGaN/p-GaN nanowires. For the S-UEM measurement, right after laser excitation, the time-resolved secondary electron images arising from the first few nm of the sample surface will be recorded, providing the image-contrast changes for mapping charge dynamics. Straightforwardly, bright or dark image contrast correspond to increase or decrease in the local electron density, telling us where the carriers (electrons/holes) are localized. In other words, bright and dark image contrast is interpreted as an increase in the local electron and hole densities, respectively. Moreover, charge separation and charge recombination can be directly accessed from the spreading out the bright contrast or from diminishing the dark contrast.​ ​​

ASP/1/1669-01-01

​Electron imaging, interface dynamics, oproelectronic applications

​With real-space imaging, we can examine the temporal behavior of a local surface area (i.e., pixel areas), providing direct information about the charge carrier dynamics including trapping and recombination on the surface and at the interface of inorganic single crystals, different structural compositions of InGaN nanowires and the electron-hole localization across the p-n junction based on GaN/InGaN nanowires. The results would help us in gaining valuable insights into the photo-physics of such materials and guide in the better designing of optoelectronic devices​

Chemical Science

Physical Sciences and Engineering

Real-Space Imaging of Perovskite Single Crystals Using 4D Electron Microscopy

Academic Program: Chemical Science

​While charge carrier dynamics in the bulk of semiconductor materials are well understood, charge transport including ejection and diffusion on surfaces and interfaces is still one of the prime challenges facing the communities of solar cells and surface sciences. Unfortunately, time-resolved laser spectroscopies that have been commonly used to understand the dynamics of photo-generated carriers in condensed matter are limited by the large penetration depth (100s of nanometers) of their pump and probe pulses, making them only sensitive to the bulk properties of the investigated materials. Only rare, bespoke techniques based on ultrafast electron microscopies offer the surface sensitivity needed to track light-triggered carrier dynamics in real-time and space, such as four-dimensional scanning ultrafast electron microscopy (4D-SUEM) which has emerged recently as a powerful tool to investigate real space-time dynamics selectively, on top surfaces of various materials with high temporal and spatial resolutions. In 4D-SUEM, an optical laser pulse at 515 nm is used to excite the material surface; a pulsed primary electron beam is then generated through a delayed UV excitation pulse at 343 nm from the cooled Schottky field-emitter tip, emitting secondary electrons from the surface of the specimen in a manner that is extremely sensitive to the local electron/hole density at the surfaces and interfaces. Time-resolved secondary electrons images produced from the excited surface are detected and then analyzed, pixel-by-pixel. In this study, we will use 4D-SUEM to selectively map surface dynamics including carrier diffusion length of the MAPbI3 single crystals with different facets and different surface treatment. We will also try to image the interface of solar cells base on these single crystals including the charge carrier ejection to the electron and hole transporting layers as well as the impact of the oxide layers on the carrier dynamics and device performance​  ​​

ASP/1/1669-01-01

​Surface Dynamics Characterization

​The finding of this project may offer a clear view of the extreme carrier diffusion behavior as a result of facet termination and surface treament. The results will be useful to address device performance bottle-necks, opening a new avenue to create MAPbI3 single crystal-based optoelectronic devices that take advantage of previously unknown, extreme surface behaviors.​ 

Chemical Science

Physical Sciences and Engineering

Model- vs. Data-Parallelism for Training of Deep Neural Networks

Academic Program: Computer Science

​Training of very large Deep Neural Networks is typically performed on large-scale distributed systems using the so-called data-parallelism approach. However, the scalability of this approach is limited by the convergence properties of the training algorithms. In this project, we willstudy a less common approach, called model-parallelism, which has the potential to overcome the convergence limitations. We will deploy and evaluate experimentally the two approaches, in order to understand the trade-offs. We will then design a hybrid method that will attempt to combine the benefits of the existing approaches.​ ​​​​​

ASP/1/1669-01-01

​Computer Science / Machine Learning

​1. Experimental evaluation of model- versus data-parallelism. 2. Design and implementation of a hybrid approach.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Design and Control of Power Conversion Systems

Academic Program: Electrical Engineering

Power conversion systems are a critical component in applications such as electric vehicles, oil & gas, solar/wind energy harvesting systems and active distribution networks. This project introduces the student to contemporary topics in the fields of electronic power conversion system design and control. Unique power converter architectures and controls will be utilized to meet specialized application requirements. The student willbeexposed to the simulation, design, prototyping and testing of a representative power conversion system.​​​

BAS/1/1678/01-01

​Electrical Engineering

​- System simulation and evaluation of simulation results- A laboratory prototype   - A detailed report covering various activities carried out (should be in the format of a research paper)​​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Continual Learning

Academic Program: Computer Science

Continual learning aims to learn new tasks without forgetting previously learned ones. This is especially challenging when one cannot accessdatafrom previous tasks and when the model has a fixed capacity. In this project, the goal is to develop and improve the capability of the machine learning methods not to forget older concepts as time passes.References[1] Arslan Chaudhry, Marc'Aurelio Ranzato, Marcus Rohrbach,MohamedElhoseiny, Efficient Lifelong Learning with A-GEM, ICLR, 2019[2] Mohamed Elhoseiny,Francesca Babiloni, Rahaf Aljundi, ManoharPaluri,Marcus Rohrbach, Tinne Tuytelaars, Exploring the Challenges towards Lifelong Fact Learning, ACCV 2018https://arxiv.org/abs/1711.09601[3] Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, Tinne Tuytelaars, Memory Aware Synapses: Learningwhat(not) to forget, ECCV 2018https://arxiv.org/abs/1711.09601[4]Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, MarcusRohrbachUncertainty-guided Continual Learning with Bayesian Neural Networks https://arxiv.org/abs/1906.02425For more references, you may visit https://nips.cc/Conferences/2018/Schedule?showEvent=10910 https://icml.cc/Conferences/2019/Schedule?showEvent=3528​​​

BAS/1/1685-01-01

​Computer Vision and Machine Learning

​Develop a working research prototype for a continual learning approach1) students should learn about machine learning, deep learning, and the respective target application chosen for the internship. 2) students are expected to show capability to go from an idea to a working prototype; pushing the limits of what the state of the art can do.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Imagination Inspired Vision

Academic Program: Computer Science

Imagination has been the source of novel ideas that enable humanity to progress at an ever-faster rate. It is also is one of the key properties of human intelligence that enables us to generate creative products like music and art. Imagination is not only helpful for creating Art and Fashion, it also helps us see the world. The goal of this project is to focus on developing techniques that empower AI machines to see the world (computer vision)orto create novel products (e.g., fashion and art), hence the name Imagination Inspired Vision.Fore more context; see my talk on this topic, recorded at the University of Southern California; https://bluejeans.com/playback/s/jC9ksXIMhbHTw25sLghFgeGoWGNHcM 9VYc6QJQ8Z0yEq9X5aogZUWJ0AwDKz8hSR Vision-CAIR group at KAUST stands for Computer Vision- "C" Artificial Intelligence Research. "C" is for Content or Creative since we cover in our lab both Vision Content AI research and Vision- Creative AI research. For more information, please visit:http://www.mohamed-elhoseiny.com/vision-cair-group​​​​

BAS/1/1685-01-01

​Computer Vision and Machine Learning

​Develop imagination inspired solutions machine learning research for helping understanding and the creation of the unseen. 1) students should learn about machine learning, deep learning, andtherespective target application chosen for the internship. 2) students are expected to show capability to go from an idea to a working prototype; pushing the limits of what the state of the art can do.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Accelerated Chemistries in High-voltage Sprays of Water

Academic Program: Environmental Science and Engineering

Electrospray ionization (ESI) is a process that entails flowing liquids though metallic capillaries, typically held at voltages > 3 kV, leading to the formation of a fine spray of charged droplets (due to the imbalance between the cohesive surface tension and repulsive electrostatics). ESI is extensively used to characterize a diverse array of solutes, from simple ions to complex macromolecular complexes, using mass spectrometry (MS) - together, the platform is known as ESIMS. In the recent years,usingESIMS, researchers have reported that a number of chemical reactions accelerate by orders of magnitude, when carried out in ESI droplets in comparison to the reactions in the bulk phase. Examples include, the phosphorylation of glucose and ribose, Pomeranz-Fritsch synthesis of isoquinoline, the reaction between o-phthalaldehyde and alanine, and the ozonation of oleic acid. However, the mechanisms underlying these dramatic rate accelerations remain hotly debated. Most recently, using a variety of experimental and computational tools, we have demonstrated that ESI of solutions of water lead to gas-phase reactions, which are not representative of the air-water interface at thermodynamic equilibrium. 1 Now, we would like to develop an reactor based on ESI to investigate acid-catalyzed reactions towards the goal of producing high-value chemicals, for instance, of interest to the pharmaceutical industry.Specifically, the Summer Intern will investigate operational parameters, including the ionic strength and pH of water, ESI voltage, coaxial gas-flow rate, length of the reactor, etc., to optimize conditions based on reactions, such as the Fries Rearrangement of phenylacetate. We will analyze the reaction products through nuclear magnetic resonance and chromatography techniques. References:1. Gallo, et al., Chemical Science (2019) DOI: 10.1039/C8SC05538F​

BAS/1/1070-01-01

​Environmental and Materials Science​

​The VSRP intern will work with a senior graduate student and learn the following skills:•     Laboratory experiments: ESI-MS, ESI reactions, voltagesources,identifying reactions of interest •     Theory: basic electrostatics, data analysis, scientific writing We expect the intern to be knowledgeable in chemical engineering, driven by curiosity, hard-working, and thrive in a multicultural work environment.​

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Liquid marbles

Academic Program: Environmental Science and Engineering

Interestingly, when a drop of water is rolled on a powder comprising hydrophobic particles, of size varying from nanometer to millimeter, particles adsorb onto the liquid-vapor interface, creating what are knownas'liquid marbles'.1 Those liquid marbles can roll around on flat surfaces - hydrophobic or hydrophilic, collide with each other without releasing water, or coalesce when pushed harder.Recently, we observed that the rates of evaporation of water from liquid marbles could be higher or lower in comparison to bare water drops depending on the choice of hydrophobic particles. To understand what factors control these phenomena, we will conduct systematic experiments varying sizes, and surface chemistries of the particles. We will also apply analytical models of mass transfer to explain the experimental findings. References:1. https://www.nature.com/articles/35082026​

BAS/1/1070-01-01

​Environmental and Materials Science

​The VSRP intern will work with a senior graduate student and learn the following skills:Laboratory experiments: wet chemistry (silanation of glass beads), optical imaging Theory: data analysis, data plottingWe expect the intern to be driven by curiosity, hard working, and thrive in a multicultural work environment.​

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

How Insects-inspired Surfaces Prevent Wetting?

Academic Program: Environmental Science and Engineering

Inspired by springtails and seaskaters, insects dwelling, respectively, inwetsoils and open oceans, we have developed textured surfaces that entrap air when submerged in water (and other liquids).1 Traditionally, to robustly entrap air underwater in microtextures, surfaces are coated with hydrophobic layers, such as perfluorocarbons and hydrocarbons. Our approach can enable any material liquid repellent. We are now investigating the time-dependence of this liquid repellent behavior.Specifically, we are testing stability of entrapped air under pressure, and also as a function of liquid vapor pressure, capillary condensation, and the dissolution of the trapped gas in the liquids. We are also exploring applications of this approach for water desalination.2 References:1.      Domingues, et al., Nature Communications (2018) 9, ArticleNumber:3606 https://doi.org/10.1038/s41467-018-05895-x2.      Das, et al., Journal of Membrane Science(2019)https://doi.org/10.1016/j.memsci.2019.117185 ​

BAS/1/1070-01-01

​Environmental and Materials Science

​The VSRP intern will work with senior Group members and learn the following skills:Laboratory experiments: contact angle cells, immersion studies, imaging (optical and confocal), microfabrication and IIID printing Theory: data analysis, data plotting. We expect the intern to be driven by curiosity, hard working, and thrive in a multicultural work environment.​​

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Diel Variations in the primary productivity of the upper ocean from autonomous glider and autonomous profiling float observations

Academic Program: Marine Science

Using autonomous gliders and profiling floats, we have investigated the interaction of physical and biogeochemical processes in the upper layers of the Red Sea. In all of these, we see distinct diel patterns of variability inkeybiogeochemical variables that include chlorophyll, suspended particles (particulate carbon), and dissolved oxygen. These processes represent the complex interaction of the daily solar cycle, nutrient supply, and physical processes that contribute to horizontal transport and vertical mixing of the water column. The goal of this study is to understand the diel variations in the key biogeochemical variables and determine how they are informing us about the primary productivity of the upper layer. The visiting student will work with existing data sets that we have been obtaining since 2013, and will also be able to participate in ongoing work that is currently ongoing within the Red Sea.​​​

BAS/1/1032-01-01

​Biological Oceanography, Primary Productivity

​1. Understand the presence and persistence of diel variability inkey biogeochemical variables that have been obtained with autonomous platforms in the central and northern Red Sea.2.   Evaluate whether it is possible from these data sets to determine ifnetprimary production is occurring, or if the system is in a static, recycling state. 3. If the outcome of this effort is deemed successful, and meaningful, we expect to include this work within a publication in which the student can participate​.

Marine Science

Biological and Environmental Sciences and Engineering

Red Sea Research Center

Microfluidics-based single-molecule fluorescence imaging of nanoscopic cellular interactions

Academic Program: BioScience

The adhesion of cells to the endothelium occurs through spatio-temporally regulated interactions that are mediated by multiple intra- and inter-cellular components. The mechanism of cell adhesion has been investigated primarily using ensemble-based experiments, which provides indirect information about how individual molecules work in such a complex system. In this project, we develop microfluidics-based in-vitro live-cell single-molecule fluorescence imaging technique to unravel nanoscopic spatiotemporal interaction between adhesion molecules during the cell migration. Specifically, we aim to address some key questions in the initial step of hematopoietic stem cell homing mediated by selectin-ligand interactions.

BAS/1/1028-01-01

​Fluorescence microscopy, Micro/nano fabrication, Optics, Biophysics, Immunology

​Development of new microfluidics-based live-cell single-molecule fluorescence imaging technique.Characterization of nanoscopic spatiotemporal interaction between selectins and their ligands occurring during the cell migration.​

BioScience

Biological and Environmental Sciences and Engineering

Development of shortwave infrared emitting fluorophores and bioimaging application

Academic Program: BioScience

One of the main challenges in applying fluorescence microscopy to large biological specimens including tissues and whole organisms, which is the latest focus in fluorescence imaging field, is the absorption and scattering of both excitation light and fluorescence emission by the specimens. Oneofthe best ways to capture high quality images through thick biological specimens is to use shortwave infrared (SWIR, 1,000-1,700 nm) fluorescence since both absorption and scattering of light are highly suppressed in this wavelength region. However, fluorophores that are available for SWIR fluorescence imaging at the moment are very limited. In this project, we develop new SWIR emitting fluorophores using conjugated polymer materials. Through in depth photophysical characterization including single-molecule SWIR fluorescence microscopy, we aim to develop new SWIR-emitting conjugated polymer nanoparticles. Based on the photophysical characteristics of the developed materials, we also aimtodevelop new SWIR fluorescence imaging techniques including time-gated imaging.

BAS/1/1028-01-01

​Fluorescence microscopy, Optics, Physics, Cell biology

​Development of new SWIR-emitting conjugated polymer nanoparticles. Detailed photophysical characterization of the developed materials.  Optimization of SWIR fluorescence microscopy system for bioimaging applications.​

BioScience

Biological and Environmental Sciences and Engineering

Numerical modeling of enhanced geothermal systems

Academic Program: Earth Science and Engineering

This research project is to apply a fully coupled mathematical model of the thermo-hydro-mechanical (THM) coupling process that may significantly influence the overall energy production processes regarding enhance geothermal system (EGS). The student interns will work together with experienced researchers at KAUST to conduct a series of parametric studies regarding EGS reservoirs under various conditions. They will also participate in various academic activities at KAUST to enhance their knowledge and understanding regarding numerical techniques and simulation applications Recommended Student Academic & Research Background:Having an education background on geomechanics and geotechnical engineering, Programming by Matlab/ C++/Fortran, Familiar with numerical simulation ​

BAS/1/1351-01-01

civil engineering, environmental engineering, petroleum engineering, mechanical engineering ​​

​1. fluid and heat transfer data with the mechanical effect of the EGS reservoirs 2. A report summarizing the research progress during the internship

Earth Science and Engineering

Physical Sciences and Engineering

Stochastic analysis of multiple fracture propagation and interaction in reservoir rocks

Academic Program: Earth Science and Engineering

This research project is to combine a numerical analysis program based on an extended finite element method (XFEM) with a stochastic fracture geometry generation program. The merger will be used to analyze different fracture propagation and interaction patterns based on different reservoir conditions. The student intern will be assigned to participate in various tasks of this project such as literature review, program development and debugging, and parametric study using the developed program. They will also participate in various academic activities at KAUST to enhance their knowledge and understanding regarding various numerical techniques and simulation applications.  Recommended Student Academic & Research Background:Subject-related engineering disciplines (Mechanical, Petroleum, and Civil Eng.) or applied mathematics, Numerical analysis, Finite element method, and Programming skills with Fortran, C/C++, Python, R, and ETC​

BAS/1/1351-01-01

​civil engineering, environmental engineering, petroleum engineering, mechanical engineering ​

​Fracture propagation analysis data correlated with different boundary and/or loading conditions, and research report or/and a scientific paper

Earth Science and Engineering

Physical Sciences and Engineering

Joint models for longitudinal and survival data

Academic Program: Applied Mathematics and Computer Science

Joint models are essential is most biomedical applications due to their ability to model two data types simultaneously. In this project, the aim istodevelop vignettes for the implementation of joint models within theR-INLAframework. The prospective candidate would gain coding skills in R and potentially develop new statistical methodologies to handle real-world phenomena within the context of joint models.​​

BAS/1/1667-01-01

​Statistics

​Vignettes for the implementation of joint models within the R-INLA framework​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Impacts of UV radiation on corals and other organisms in the Red Sea

Academic Program: Marine Science

UV radiation has been identified as a key abiotic stressor in the marine environment, particularly in waters characterized by high optical transparency. One such environment is the Red Sea basin that, due to consistently minimal concentrations of UV-attenuating substances, has an exceptionally high transparency to UV radiation. This optical property and the proximity of the basin to the equator means that Red Sea organisms are exposed to intense, damaging levels of UV radiation.This project will investigate the effects of UV on scleractinian corals and other organisms in the Red Sea. ​

BAS/1/1072-01-01

​Marine Science

​Bibliographic search and bibliometric analysis.Design of field and laboratory experiments.Apply molecular laboratory techniques to evaluate UV effects on e.g. DNA damage, symbiosis state, lipid peroxidation, etc.Write final report summarizing the project work and key findings.

Marine Science

Biological and Environmental Sciences and Engineering

Red Sea Research Center

Biological stability of chlorinated and non-chlorinated drinking water

Academic Program: Environmental Science and Engineering

Drinking water is distributed from the treatment facility to consumers through extended man-made piping systems. The drinking water system should be microbiologically safe and biologically stable (WHO, 2006). The biological stability criterion refers to maintaining the microbial drinking water quality in time and distance from the point of drinking water production up to the point of consumption. This research will be conducted at the unique drinking water distribution system (DWDS) at KAUST a confined network of the same age supplied with reverse osmosis (RO) based drinking water. The aim of the project is to characterize temporal and spatial dynamics in biofilms and microbial community in the water from source to tap with the considerations of the impact of residual disinfectant use The results will allow better understanding whether residual chlorine is needed for distribution of RO produced drinking water and will lead to better insights on the biological stability of the produced water. ​

BAS/1/1024-01-01

​Chemistry, environmental science

Operate miniature drinking water distribution networks (preparation of solutions, setting up  and run equipment, problem solving) Sample analysis (biological and chemical analysis, DNA extraction, etc.Data analysis Written and oral presentation of (intermediate) results.​

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Characterization of biofilm growthrate in a membrane system

Academic Program: Environmental Science and Engineering

Membrane filtration plays an important role in seawater desalination and wastewater reclamation. Biofouling is an unacceptable loss of performance caused by the growth of bacteria inside the membrane element. The aim of the project is to establish relations between operational conditions, such as water velocity, production rate and nutrient concentration and the growth rate of biofilms. The results will allow better understanding and control of biofouling formation. The two main methods to observe the thickness of the biofilm are via its hydraulic resistance and via optical coherence tomography (OCT). ​

BAS/1/1024-01-01

​chemical engineering, environmental science, etc

​Formulate a research question and design the experiments accordingly.Run experiment (preparation of solutions, setting up and run equipment, problem solving, OCT-scan of biofilm)​Data analysisWritten and oral presentation of (intermediate) results.

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

3D Bioprinting of Cell-Laden Microgels for the General Construction of Vascularized Tissue Structures and Organoids

Academic Program: BioScience

3D bioprinting is a fabrication technology that aims to produce complex 3D functional living tissues suitable for disease modeling and even organ transplantation. Consequently, this technology has gained strong interest in areas such as tissue engineering and regenerative medicine. It is believed that 3D bioprinting gives promising solutions to solve the organ shortage for transplantation and to bridge the gap between 2D cell culture and live tissue experiments. In 3D bioprinting technology, biomaterials and cells are printed together to produce viable tissue-constructs with different shapes and sizes at the micro- and macro-scale level. However, 3D bioprinting technology is currently facing problems in terms of poor performance in shape fidelity of the 3D constructs, biocompatibility, and vascularization. These drawbacks could arise from the biomaterial and the bioprinting method used. For instance, synthetic polymers lack cell adhesion motifs while naturally derived materials lack appropriate mechanical strength. Moreover, most of the bioprinting methods rely on UV- or chemical crosslinking that could be harmful to the cells. To overcome these problems, we have developed a 3D bio-printing method to print under physiological conditions using self-assembling ultrashort peptides (SUP) as bioinks. SUP are natural peptides that are chemically synthesized and can be tailored to include biological and physicochemical cues for the improvement in biocompatibility and shape fidelity of the 3D construct. Nevertheless, our bioprinting approach still has technical challenges in controlled cell distribution and vascularization. To address these issues, we are working on the incorporation of SUP microgels covered by endothelial cells into the 3D bioprinting process to drive the cell to cell connection among microgels. ​​​​

BAS/1/1075-01-01

​Materials Science

​Print self-assembling ultrashort peptides (SUP) as bioinks​

BioScience

Biological and Environmental Sciences and Engineering

Computational Bioscience Research Center

Modelling and numerical simulation

Academic Program: Applied Mathematics and Computer Science

There are several modelling and simulation projects available. Topics of the projects are 1. Modelling biogas fermentation, 2. Multiscale modelling of permeation through human skin, 3. HPC based simulation of signal processing in neurons, 4. Numerical methods for free surfaces, 5. Simulation of energy storage. The models we used are based on first principles from Physics, typically resulting in systems of PDE. They all are solved using the same software tool UG4, providing advanced numerical methods like parallel adaptive multigrid solvers.​

BAS/1/1674-01-01

​Computational Science, Mathematics, Computer Science, Sciences, Engineering

​Setting up, discretising and models on the basis of first principles. We expect the students to have a solid knowledge in analysis, numerics and programming.​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Extreme Computing Research Center

MPS modelling of carbonate rocks

Academic Program: Earth Science and Engineering

The project is focused on 3D geocellular modelling of modern and ancient carbonate rocks. Applicant we use two data sets, (1) modern carbonates and (2) Jurassic carbonates, to develop a new workflow for multiple point statistics.

BAS/1/1399-01-01

​Carbonate Geology and Modelling

​Outcome of the study will help to improve the prediction of potential reservoir heterogeneities in carbonate reservoirs​

Earth Science and Engineering

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Vertical and Lateral Heterogeneity in Unconventional Source Rock Sequences

Academic Program: Energy Resources and Petroleum Engineering

Economic production of a hydrocarbon reservoir is critically influenced by a good understanding of the distribution of litho- and organo-facies, porosity, geochemical and geomechanical properties of the reservoir layers. This, in turn, is primarily a function of both the vertical and lateral heterogeneity in the distribution and geochemical composition of soft organic-rich layers and more brittle organic-lean layers, taking in an account the regional assessment of the stress regime, heatflow and thermal conductivity. The proposed study will help to conduct a detailed assessment on a production scale of depositional and geochemical heterogeneities with unconventional development scenarios. The main aim of this research project is to describe and analyze the vertical and lateral heterogeneities of unconventional reservoirs through outcrop analogue investigations, in order to: 1. characterize the lateral and vertical changes in cyclicity and its impact on the occurrence, distribution and geochemical composition of organic-rich and organic-lean facies in a basinal setting; 2. provide based on the results of the fieldwork an assessment of possible variations in production behaviour of unconventional reservoirs in rocks of similar origin. The candidate will perform, along with fieldwork, a variety of microscopic and geochemical analyses on systematically collected sample from different outcrops exposing the Upper Cretaceous-Eocene Rocks of Jordan, which has a great potential as an unconventional reservoir.​​​​

BAS/1/1399-01-01

​Geology, Carbonate Geology, Sedimentology, Stratigraphy, Unconventional Source Rocks, Facies Analysis

​1. The project will form a Masters Thesis of the proposed student. 2. The results will published in peer reviewed Journals. 3. The results will be presented in international conferences.​ 

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Micritization under elevated temperature and pressure

Academic Program: Applied Mathematics and Computer Science

Microrhombic calcite crystals, which form the frame of microporosity in most Middle Eastern carbonate reservoirs, formed at temperatures of 60°Cto 80°C and a burial depth in excess of 1km (Vahrenkamp et al., 2014; Swart et al., 2016). Since there are possibilities by some initial experimentson the ability of microbes to be alive and perform diagenetic alterations at elevated temperatures and pressure (Daffonchio and co-workers,unpublished data; see preliminary data below), we propose to investigate whether microbes are involved in the generation of those microrhombiccrystals through microbial diagenesis of previous micritized sediments. ​​​​

BAS/1/1399-01-01

​Geomicrobiology

​• Micritization experiments will be simulated at burial diagenetic conditionsof high hydrostatic pressure (HP: 0.1 - 25 MPa) and temperature (T: 10 - 70°C) in bioreactors • The activity of several bacterial strains from pure and mixed culture collections (e.g., Escherichia coli) and/or those obtained from the sediments in Task 3.2 will be tested at different conditions of HP. • Growth of cells will be measured by bacterial counts after fluorescence in situ hybridization (FISH) staining coupled with flow cytometry. ​

Applied Mathematics and Computer Science

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Pleistocene to Holocene sediment dynamics of the Al Wajh Bank slope (Red Sea)

Academic Program: Earth Science and Engineering

The objective of this project is to describe and analyse three soft sediment cores from the Al Wajh Bank slope (Red Sea). Based on core description, dated ages and grain size analysis, the candidate will establish a depositional model. To achieve this goal soft sediment cores and a bathymetry data have to be analysed.

BAS/1/1399-01-01

​Geology – Marine Geosciences, Carbonate Sedimentology

​(1)The findings will improve the fundamental understanding of land-attached carbonate platform sediment export dynamics and (2) the impact of sea-level variations in the Red Sea Rift basin setting.​

Earth Science and Engineering

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Expression, Purification, Characterization of Proteins for Biocatalysis

Academic Program: BioScience

A fluorescent protein variant was tailor-made as a suitable host for the incorporation of artificial metal centers through in silico removal of metal binding motifs and improvement of thermal, salt and solvent stability. These new metalloproteins possess reactivities nature does not provide. The further goal will be the examination of the new metalloprotein in aqueous catalysis reactions and the examination of the influence of further mutations on selectivity and reactivity.Project-duration will be 3-6 month, details of arrival/departure dates to be discussed. ​​

BAS/1/1385-01-01

dominik.renn@kaust.edu.sa

Chemical Science

​Chemistry/Biochemistry/Molecular Biology

​Students shall extend their general knowledge and skills in molecular biology and protein biochemistry. An emphasis will be put on expression, purification and characterization techniques. If capable mutant proteins will be crystallized to determine structural properties. Students will be taught to work independently on projects, yet strengthening their critical sense to develop new ideas. In the course of the internship students shall demonstrate this understanding during oral presentations and one final written report.

BioScience

Physical Sciences and Engineering

Undergraduate

KAUST Catalysis Center

Functionalization of Gas Vesicles

Academic Program: BioScience

Extremozymes, produced by extremophiles, show remarkable abilities that can revolutionize the chemical, biotechnological, bioremediation, agricultural and pharmaceutical industries. At present, only minor fractions of the extremophiles on Earth have been exploited. Both bioprospecting and protein engineering are potent tools for discovering new extremophilic enzymes that meet ever-evolving industrial and biotechnological needs. During the internship interns will work on projects spanning the whole breadth of protein science and enzymology, starting from cloning, protein expression and purification, protein engineering and characterization using various biochemical and biophysical techniques.

Our internship opportunities are the gateway for your entry into the exciting world of proteins science by enabling you to put your academic training and passion for bioscience research. Project-duration will be 3-6 month, details of arrival/departure dates to be discussed.

BAS/1/1385-01-01

dominik.renn@kaust.edu.sa

Bioscience

​Chemistry/Biochemistry/Molecular Biology

​Students shall extend their general knowledge and skills in molecular biology and protein biochemistry. An emphasis will be put on expression, purification and characterization techniques. If capable mutant proteins will be crystallized to determine structural properties. Students will be taught to work independently on projects, yet strengthening their critical sense to develop new ideas. In the course of the internship students shall demonstrate this understanding during oral presentations and one final written report.

BioScience

Physical Sciences and Engineering

Graduate

KAUST Catalysis Center

Visible-light Photoredox Catalysis Transformations

Academic Program: Chemical Science

Over the past few years, the field of photocatalysis has demonstrated its potential to drive complicated chemical reactions under mild conditions using visible-light as an energy source and inexpensive, bench-stable substrates as feedstocks. Our group has been focused on the development of photocatalyzed organic transformations via diverse pathways including single electron transfer (SET), energy transfer (ET), photo-excited metal cross-coupling, electron-donor-acceptor (EDA) complex. Project-duration will be 3-6 month, details of arrival/departure dates to be discussed.

BAS/1/1385-01-01

dominik.renn@kaust.edu.sa

bioscience

​Chemistry/Biochemistry/Molecular Biology

​Students shall extend their general knowledge and skills in organic chemistry and catalysis. An emphasis will be put on the synthesis and application of new photocatalysts. Students will be taught to work independently on projects, yet strengthening their critical sense to develop new ideas. In the course of the internship students shall demonstrate this understanding during oral presentations and a final written report.

Chemical Science

Physical Sciences and Engineering

Graduate

KAUST Catalysis Center

Tackling the challenges of OH-Laser Induced Fluorescence technique on detonation: numerical approach to improve experimental design

Academic Program: Mechanical Engineering

Context: Compared to classical constant volume or constant pressure thermodynamic cycles, the detonation regime of combustion could increase by 40% the efficiency of engines. In line with the Paris agreement, identifying more efficient combustion processes is one of the strategies to limit CO2 emissions that contribute to climate change. In parallel to its promising application to the energy production field, detonation studies have also regained interest for safety applications, due to the last nuclear accident in Fukushima. Thus, two aspects can be distinguished: for transportation, researchers are focused on obtaining and controlling a self-sustained detonation in a specific engine (PDE or RDE), while for industrial safety, researchers are focused on identifying the detonation limits and the quenching mechanism of detonation to prevent them. While the measurement of temperature and chemical species is of current practice in conventional combustion process (flames, engines, etc…), the experimental characterization of detonation relies on the determination of the detonation velocity, global pressure, and density gradient structure. These information are limited to validate numerical simulations and to be confident in the phenomenological comprehension extracted from it. While planar laser-induced fluorescence of hydroxyl radical (OH-PLIF) is a powerful technique to characterize reaction fronts, previous studies have shown significant limitations of this technique for detonation visualization. Not only restricted to reaction front visualization, this technique is also of interest as it can give access to 2-D temperature measurements in detonations

BAS/1/1396-01-01

Mechanical engineering, chemical engineering, aerospace engineering

​First, the student will have to become familiar with the principle of the OH-PLIF technique and the particularities associated with its usage on detonations, which has high pressure and temperature variations, high-speed flow (up to 2000m/s), etc… Second, the sensitivity analysis of the fluorescence signal will be conducted to identify the most sensitive parameters of the PLIF signal. Third, optimal operating conditions (≠ maximizing the fluorescence signal) will be identified and tested experimentally. Due to both the strong non-linearities between the PLIF signal intensity and each parameter involved, machine-learning approaches may be used to facilitate the identification of the optimal operating conditions​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Temperature of hydrogen-air detonations: measurements by 2-color planar laser induced fluorescence of the hydroxyl radical

Academic Program: Mechanical Engineering

Compared to classical constant volume or constant pressure thermodynamic cycles, the detonation regime of combustion could increase by 40% the efficiency of engines. For a long time restricted to military applications, due to the global energetic issue, the civil applications of detonations have received in increasing interest during the last decade. One of the main challenges in this research field is to obtain a self-sustained detonation for practical fuel-oxidizer mixtures (e.g. kerosene-air), in a setup with typical dimensions comparable to those of a commercial gas turbine. While the quantitative characterization of flames in terms of temperature and chemical species is of current practice, the experimental study of detonation properties is mainly restricted to the determination of the detonation velocity, global pressure, and density gradient structure. Information such as the temperature or density of hydroxyl radical fields in a detonation front have never been measured. However, to better understand the detonation mechanisms and to help in validating detonation models and numerical simulations, these data are crucial.  Objectives:  In this context, the main objective of the project is to adapt a non-intrusive thermometry technique broadly used in the combustion community, the 2-color planar laser induced fluorescence on OH, to the characterization of an H2 – air detonation. There are many challenges to obtain reliable temperature measurements of a detonation front, including single shot measurements, synchronization, spectroscopic properties of OH in the condition of the detonation front, etc.  ​​​​​​

ASP/1/1669-01-01

​Mechanical Engineering, Combustion, Fluid Mechanics

​First, the student will learn the 2-color PLIF technique on OH in a well characterized configuration: a stable flat flame stabilized over a McKenna burner. During this preliminary step, the uncertainty of the measurements, averaged and single shot, will be characterized. Second, the system will be implemented on a 2D detonation test rig, equipped with optical access for laser diagnostics. One of the main challenges will be the synchronization of the PLIF system with the detonation front arrival in the measurement area. Indeed, the detonation front propagates at a speed of about 2000 m/s, and the jitter between two events in the arrival of the measurement area can be as large as 1 ms. Synchronization will require time of flight measurements and analysis of the detonation propagation front. Finally, post processing of the OH PLIF images will be performed in order to determine the temperature fields. Due to the complexity of the detonation setup and combined laser diagnostics, the experimental part of this study will be performed by two persons: the intern student and an experienced researcher (senior PhD student or post-doc).​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Gradient compression for distributed training of machine learning models

Academic Program: Computer Science

Modern supervised machine learning models are trained using enormous amounts of data, and for this distributed computing systems are used.Thetraining data is distributed across the memory of the nodes of the system, and in each step of the training process one needs to aggregate updates computed by all nodes using local data. This aggregation step requires communication of a large tensor, which is the bottleneck limiting the efficiency of the training method.To mitigate this issue, various compression (e.g., sparsification/quantization/dithering) schemes were propose in the literature recently. However, many theoretical, system-level and practical questions remain to be open.In this project the intern will aim to advance the state of the art in some aspect of this field. As this is a fast moving field, details of the project will only be finalized together with the successful applicant.Background reading based on research on this topic done in mygroup: https://arxiv.org/abs/1905.11261https://arxiv.org/abs/1905.10988 https://arxiv.org/abs/1903.06701 https://arxiv.org/abs/1901.09437 https://arxiv.org/abs/1901.09269https://www.frontiersin.org/articles/10.3389/fams.2018.00062/abstract  https://arxiv.org/abs/1610.05492https://arxiv.org/abs/1610.02527​

BAS/1/1677-01-01

​computer science, mathematics, machine learning

​Ideally author or coauthor a research paper, and submit it to a premier conference in the field (e.g., ICML, AISTATS, NeurIPS, ICLR).​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Towards a Principled Understanding of Deep Learning

Academic Program: Computer Science

Deep learning models provide state of the art performance on many practical machine learning tasks. However, there is a large gapbetweenour theoretical / conceptual understanding and practice.The intern will work in one of the follow areas, depending on interest and background: - deep learning models- adversarial attacks and robustness- optimization for deep learning- generalization of deep learning- GANs- model compression

BAS/1/1677-01-01

​computer science, mathematics

​Ideally contribution to a research paper​.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Federated Learning

Academic Program: Computer Science

Federated Learning (FL) enables mobile phones to collaboratively learnashared prediction model while keeping all the training data on device, decoupling the ability to do machine learning from the need to store the data in the cloud. This goes beyond the use of local models that make predictions on mobile devices by bringing model training to the device as well.FL was co-invented by my former student Jakub Konecny, myself and Google. We have launched. a FL system in 2017, it is now in use in more than 1 billion Android devices:https://ai.googleblog.com/2017/04/federated-learning-collaborative.html https://ai.google/research/pubs/pub45648 In this project we will investigate further improvements and applications of FL.​​​​

BAS/1/1677-01-01

​Machine Learning

​Ideally a joint research paper.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Topics in Machine Learning and Optimization

Academic Program: Applied Mathematics and Computer Science

Topics in machine learning (ML). The project can be of a theoretical nature (e.g., design of optimization algorithms for training ML models; building foundations of deep learning; distributed, stochastic and nonconvex optimization), or of a practical nature (e.g., creative application and modification of existing techniques to problems in federated learning, computer vision, health, robotics, engineering). The precise topic will be decided together with the successful applicants, and will be tailored to their skills and background.

ASP/1/1669-01-01

​Computer Science, Mathematics or a related discipline

​Original research – contribution to a research paper​.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Nanovisualization

Academic Program: Computer Science

During the research internship students will learn about the nanovisualization technology which combines computer graphics and visualization for nano-structures in life sciences and biotechnology. Nanovisualization poses several new technological challenges that are not reflected in the state of the art computer graphics and 3D visualization as of today. The underlying domain requires new techniques for multi-scale, multi-instance, dense, three-dimensional models which we never subject of technological advances in 3D graphics before. These scenes are of gigantic sizes and unmatched complexity. Therefore the task in nanovisualization is to thoroughly revisit all technological aspects of rendering, visualization, navigation, user interaction, and modeling in order to offer algorithmic solutions that address new requirements associated with the nano and microscopic scales.Throughout their stay, students will be working in team with researchers on specific assignment for a particular scientific work or solving a technical challenge in the field of computer graphics and visualization. Nanovisualization is one of the key components in creating, studying, and understanding scale-wise small (but complex) systems. As such it will become a key technology in the upcoming industrial revolution that will be heavily associated with the nano scale.The benefit for the students is to get familiar with nanovisualization research field, which is worldwide uniquely offered at KAUST. They will be integrated in working on a very important problems so far untouched in graphics and visualization that are very relevant for many societal challenges from the health, food, and energy sectors.

ASP/1/1669-01-01

ivan.viola@kaust.edu.sa

Nanovisualization

​computer science, applied mathematics, physics

​Students should work on an internship project and should implement a clearly specified task. It is expected that students are familiar with computer graphics and visualization and can document advanced skills in graphics programming​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Visual Computing Center

Mapping protein complexes in vivo

Academic Program: Plant Science

During multicellular development, the specification of distinct cell fates is often regulated by the same transcription factors operating differently in distinct cis-regulatory modules. In the model plant Arabidopsis root, distinct cell types are determined by the interacting transcription factors within one contiguous tissue layer. Using fluorescence lifetime microscopy we revealacell type-specific protein complexes that differentially regulate target genes and instruct distinct cell fates. In addition to determining the network function in other organs, we are currently studying how are these complexes established and maintained by generating a temporal interaction map and dissecting the transcriptional regulation by these complexes.We will use the following tools: FRET-FLIM, confocal microscopy imaging, mutants analysis.​

BAS/1/1081-01-01

​Developmental biology, cell biology

​Generate a spatio-temporal protein interaction map in vivo​

Plant Science

Biological and Environmental Sciences and Engineering

Center for Desert Agriculture

Molecular mechanisms underlying growth and defense in plants

Academic Program: Plant Science

When attacked by pathogens, plants allocate their energy and resources into defense responses at the expense of growth. Hence, understanding the mechanisms by which plants prioritize their responses is instrumental for improving plant defense and growth and consequently increasing crop yield. Recently, we have established a link between the defense hormone Jasmonic Acid (JA) and a transcription factor pathway with key roles in development. We have found that the developmental regulators BIRD proteins mediate Jasmonic acid defense response through interacting with core JA signaling pathway genes. The project aims to dissect the molecular framework underlying the dual function of these protein complexes. The identified signaling networks and pathways can then be rewired to allow simultaneous growth and defense. we will use the following tools: RNAseq, genome editing tools, fluorescence microscopy imaging amd a range methods for detecting protein-protein interactions in vitro and in vivo.

BAS/1/1081-01-01

​Developmental biology, cell biology

​The gained knowledge will be used to generate resistant crops with optimal growth behavior using genome editing tools.​

Plant Science

Biological and Environmental Sciences and Engineering

Center for Desert Agriculture

Spatio temporal analysis of expression of genes controlling assymetric stem cell division and tissue patterning in plants

Academic Program: Plant Science

BIRDs nuclear factors have been described to regulate root growth through association with the transcription factors SCARECROW and SHORTROOT, however their function in other organs remain to be elucidated. Here we propose to dissect network function in lateral roots and leaves. We will determine their physical associations spatially and during different developmental stages. We will also assess whether their target are regulated similarly.Objectives: In this project we aim to dissect how BIRD proteins regulate leave tissue patterning and map their localization in different mutant backgrounds. In addition, we will dissect binding sites in different target genes and alter specific binding by site directed mutagenesis. Technologies: confocal imaging microscopy, site directed mutagenesis, promoter activities using dual luciferase, plant phenotyping, cloning using gateway technology ​

ASP/1/1669-01-01

​Plant Biology​

​Map the expression of the genes at different developmental stages and dissect thein binding motifs

Plant Science

Biological and Environmental Sciences and Engineering

Center for Desert Agriculture

Large-Scale Scientific Visualization

Academic Program: Computer Science

Develop large-scale visualization approaches. Our focus areas are visualization of extreme-scale data, volume visualization, flow visualization, differential geometry and mathematical physics in visualization, large-scale image and volume processing, multi-resolution techniques, data streaming and out-of-core processing, domain-specific languages for visual computing, interactive segmentation, and GPU algorithms and architecture. See more information on http://vccvisualization.org  ​​

ASP/1/1669-01-01

​Scientific visualization

S​oftware prototype, project report.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Experimental study of carbon-free combustion

Academic Program: Mechanical Engineering

A major goal of combustion research is to reduce emissions and minimize the harmful impact of energy production and transportation on the environment. Advancements in combustion sciences enabled strong reduction of NOX, SOX and particulates. The challenge for the next decade is reduction of carbon dioxide. One strategy is to completely remove carbon from the fuel, using carbon-free hydrogen carrier such as ammonia. Combustion of ammonia is not well understood, and no detailed information on the flame of ammonia-air flames is available. In this project the student will perform 1D Raman measurements of temperature and major species in ammonia flames in collaboration with a postdoc or a Ph.D. student. ​​​​​​

BAS/1/1388-01-01

​Mechanical, Aerospace, Chemical Engineering or Applied Physics

​The student will learn the fundamental of laser spectroscopy, and will gain hands-on experience in the operation of ammonia burners, and advanced laser diagnostics. He will acquire and analyze unique experimental datasets, and advance the understanding of combustion of ammonia-air flames.  ​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Passivation in Perovskite Solar Cells

Academic Program: Materials Science & Engineering

Perovskites are an emerging class of materials which offers a high-efficiency photovoltaics owing to its appealing optical and electronic properties. However, defects such asnon-coordinated ions at their grain boundaries and surfaces do contribute to non-radiative photo-carrier recombination. This undesirably inflates theopen-circuit voltage deficit and is a likely contributor to the widely reported phenomenon ofhysteresis in the current-voltage characteristics which is set to remain at the forefront of thecontinuing progress towards to the theoretical PCE limit of 30%. In this project, the candidate will have an opportunity to explore some new interfacial engineering strategies, such as surface passivation, grain boundary passivation and contact passivation to eliminate the defects. This will help to increase the open circuit voltage of the perovskite devices which will be employed to achieve champion perovskite/silicon tandem solar cells. At the end of the internship, the candidate(s) will be experienced the full processing steps of the perovskite solar cells and they may have an opportunity to publish the findings in well-respected scientific journals.​​

BAS/1/1387-01-01

​Solar Cells

​Exploring new passivation moleculesTesting conductive polymers which has carboxyl groups for passivation purpose Testing 2D perovskites for interface passivation purposeAchieving >1.2V open circuit voltage for 1.6 eV perovskite absorbers based solar cells

Materials Science & Engineering

Physical Sciences and Engineering

KAUST Solar Center

Thermal Evaporation of Perovskite Absorbers for Silicon Perovskite Tandem Solar Cells

Academic Program: Materials Science & Engineering

Perovskite/silicon tandem solar cells are very promising technology to achieve >30% power conversion efficiency target. Despite this technology features promising efficiency potential, several challenges need to be overcome prior to possible industrial application. A particular challenge relates to the fact thatto maximize the light coupling into the bottom cells, the tandems require so-called random-pyramid textured bottom cells (with a feature size of several micron, see Fig. 1a). Whereas flat substrates have enormous reflection losses (Fig. 1c), textured substrates enable improved light coupling into the silicon wafers. Textured silicon solar cells are the industrial state-of-the-art, and there is likely little incentive to develop processes on expensive mirror-polished wafers. However, due to the characteristics of textured surfaces, which present irregularities and low-wetting properties, conventional solution techniques cannot be used to deposit the perovskite or the extraction layers.From this, it can be readily understood that the top cell fabrication needs to rely on scalable and conformal deposition methods, with a high degree of uniformity and reproducibility.  For these reasons, we aim in this project to alter our current state-of-the-art solution-based PSC processing procedures as much as possible towards scalable vacuum-based techniques. In this projects, the candidate will perform an evaporation of perovskites precursors and the conversion of the layers will be performed either by co-evaporation or vacuum/solution hybrid based methods. At the end of the internship period, students will learn how to fabricate and optimize perovskite solar cells. The candidate will have a chance to experience the fabrication of fully textured silicon/perovskite tandem solar cells.Why thermal evaporated perovskites?Scalability: vacuum based deposition techniques are a well-established technique in several industrial processes.Reproducibility: thermal evaporation process of perovskite absorbers is not affected by the multitude of uncontrollable parameters typical for solution-processed perovskites.Uniformity: unlikely solution deposition, evaporation enables uniform deposition, independently from the substrate type.Low thermal budget: thermal evaporation is a low-temperature process and the substrate can be eventually further cooled to room temperature.Environmentally benign: evaporation does not involve toxic solvents.Process flexibility: different perovskite composition can be obtained by evaporation, according to the desired application. ​

BAS/1/1387-01-01

​Solar Cells

​Thickness control of the evaporated lead iodideOptimization of co-evaporated of lead iodide and cesium bromide Process sophistication for triple cation system perovskites>23% tandem solar cell efficiency using thermal evaporated perovskites​

Materials Science & Engineering

Physical Sciences and Engineering

KAUST Solar Center

Broadband Transparent Front Electrodes for Perovskite Silicon Tandem Solar Cells

Academic Program: Materials Science & Engineering

This project is focusing on developing novel transparent electrodes for perovskite/silicon tandem solar cells whichare anemerging class of solar cells technology. Perovskite/silicon tandem solar cellsaim to achieve the power conversion efficiencies beyond the single junction limit of the silicon solar cells. Towards this end, developinghighly transparent electrodes are critical for the maximized light harvesting since parasitic absorption loses originating from the transparent conductive oxides causes drastic current losses. In this project, the deposition of the novel transparent conductive oxides will be performed the sputtering technique. The candidate will gain experience on the structural, optical and electrical and characterization of the thin films. Moreover, the candidate will have experience in the fabrication and characterization of the perovskite/silicon tandem solar cells to test the developed materials. Why we need broadband transparent electrodes on perovskite/silicon tandem solar cells?In perovskite/silicon tandem solar cells, the perovskite top cell efficiently harvests the blue part of the solar spectrum, while transmitting the red part, which is absorbed in the silicon bottom cell. In this way, the tandems can overcome the single-junction efficiency limit of silicon solar cells. However, parasitic absorption losses originating from the transparent electrodes hinders the light harvesting. Typically, a front transparent electrode in any solar cell has a sufficiently large (>3 eV) optical band gap to avoid absorption losses in the visible range of the spectrum. This requirement is already fulfilled by several TCOs such as ITO, IZO, and IO: H. For perovskite/silicon tandem solar cells, transparent electrodes with low absorptance in the NIR‐IR part of the spectrum are required since these devices use optical absorbers that are active in this range of the spectrum. Towards reaching >30% photoconversion efficiency, designing transparent electrodes with exceptionally large broadband transparency carriers critical importance. References[1] Morales‐Masis, M., De Wolf, S., Woods‐Robinson, R., Ager, J. W., & Ballif, C. (2017). Transparent electrodes for efficient optoelectronics. Advanced Electronic Materials, 3(5), 1600529.​

BAS/1/1387-01-01

​Solar Cells

​Optimization of the sputtering parameters of H:In2O3 and IZO transparent electrodesOptical and electrical characterization of the fabricated films Achieving <20 ohm/sq. sheet resistivity for 1000 nm thickness together with broadband transparency (<10% absorbance within this region).Exploring new TCO by metal doping of In2O3​

Materials Science & Engineering

Physical Sciences and Engineering

KAUST Solar Center

Novel Electron and Hole Transport Layers by Atomic Layer Deposition Technique for Perovskite Silicon Tandem Solar Cells

Academic Program: Materials Science & Engineering

The atomic layer deposition (ALD) technique is an efficient technique to deposit thin films at low temperature, which is based on self-limiting surface reactions by exposing sequentially on the substrate with various precursors and reactants. It provides excellent control over film thickness at the angstrom or monolayer level and deposition on high aspect ratio nano andmicrostructures with excellent step coverage. To exploit these advantages, we are employing ALD deposited electron and hole transport layers on randomly textured silicon wafers. In this project, to increase the light coupling in the tandem solar cells, the deposition of the broadband transparent electron and hole transport layers will be performed by the ALD technique. The candidate will gain experience on the structural, optical and electrical and characterization of the thin films by optimizing the deposition recipes. Moreover, the candidate will have experience in the fabrication and characterization of the perovskite solar cells and will have an opportunity to experience the fabrication of perovskite/silicon tandem solar cells. Why Silicon/Perovskite Tandems?The current global photovoltaics market (nowadays taken for more than 90% by crystalline silicon solar cells) has seen a sustained growth of its production capacity by more than 20% annually [1]. From a longer-term perspective, the market is expected to make a transition towards ultra-high efficiencies. For this, further efficiency improvement s will be needed, beyond the single-junction efficiency limit of silicon [2].  The most straight-forward way to do so is in the form of a silicon-based tandem solar cell, where a wider-bandgap top cell overlays the silicon bottom cell. In perovskite/silicon tandem solar cells, the perovskite top cell efficiently harvests the blue part of the solar spectrum, while transmitting the red part, which is absorbed in the silicon bottom cell. In this way, the tandems can overcome the single-junction efficiency limit of silicon solar cells. References[1] Haegel, Nancy M., et al. "Terawatt-scale photovoltaics: Trajectories and challenges." Science 356.6334 (2017): 141-143. [2] Richter, A., Hermle, M., & Glunz, S. W. (2013). "Reassessment of the limiting efficiency for crystalline silicon solar cells." IEEE Journal of Photovoltaics, 3(4), 1184-1191.​​​

BAS/1/1387-01-01

​Solar Cells

​Optimization of SnO2 thin films for perovskite solar cells applicationsTesting these layer for flat junction opaque devices for performance analysis Achieving >23% tandem solar cells efficiency using these buffer layers.Testing new ALD precursors for electron and hole transporting purposes

Materials Science & Engineering

Physical Sciences and Engineering

KAUST Solar Center

Salinity Tolerance of Plants

Academic Program: Plant Science

Soil salinity is a major abiotic stress constraining crop production. We are investigating how some plants are able to cope with salt stress, to then inform research on other crops to make them more tolerant to salinity stress. Quinoa (Chenopodium quinoa) tastes good, is highly nutritious and is a very salt tolerant crop; however, we are yet to discover the mechanisms for its high salt tolerance. This is one species that we are currently studying. We are also looking at mechanisms of tolerance in wild relatives of domesticated crops, in particular wild tomatoes and wild barley.​​

BAS/1/1038-01-01

mark.tester@kaust.edu.sa

Salinity

​Biology, Computer science

​Lots of good research / lots of hard work and fun.​

Plant Science

Biological and Environmental Sciences and Engineering

Undergraduate

Center for Desert Agriculture

Novel Ultrashort Peptide Nanogels Generate Silver Nanoparticles to Combat Emerging Antimicrobial Resistance Strains

Academic Program: Computer Science

Ultrashort linear peptides consisting of 3–7 natural amino acids self-assemble to helical fibers within supramolecular structures. The amphiphilic peptide motif, – a hydrophobic tail and a hydrophilic head group-, facilitates self-assembly via parallel-antiparallel α-helical pairs and subsequent stacking into β-turn fibrils. Aggregation of fibrils into fibers results in the formation of nanogels scaffolds capable of entrapping up to 99.9% water. During self-assembly, these ultrashort peptides form meshed 3D nanofibrous networks that extend into the micro-scale length.Nanogels made from self-assembling ultrashort peptides (4-6 amino acids in size) are promising biomaterials for various biomedical applications such as tissue engineering, drug delivery, regenerative medicine, microbiology and biosensing. We have developed silver-releasing peptide nanogels with promising wound care applications. The peptide nanogels allowed a precise control of in situ synthesized silver nanoparticles (AgNPs), using solely a short exposure to UV radiation and no other chemical reducing agent. We propose these silver-releasing nanogels as excellent biomaterial to combat emerging antimicrobial resistant strains.​​​​

BAS/1/1675-01-01

​Self- assembly, tissue engineering, nanogels, silver nanoparticles, antimicrobial agents

​Generation of silver nanoparticles in situ (Hauser), computational studies on kinetics and size of nanoparticle formation under restricted conditions (Michels), study of nanofiber networks by computational dynamics (Michels) and by bioimaging techniques ( electron microscopy (SEM, TEM)) (Hauser), CD and FT-IR spectroscopy to follow up on nanofiber formation (Hauser)​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Developing an In Vitro 3D Tissue Model for Studying Alzheimer’s Disease

Academic Program: Computer Science

Alzheimer’s disease is a degenerative disease where patients gradually lose their memory and cognitive skills due to the death and degeneration of neurons. Neurons are the cells responsible for transmitting information inside the brain through electrical charges and neurotransmitters, which are chemicals that flow across the synapses between each neuron. The main features of Alzheimer’s disease is described to be the formation of abnormal structures called beta amyloid plaques (formed outside of the cells) and neurofibrillary tangles (formed inside the cells). These plaques and tangles damage the interior and structure of neurons, causing their destruction and demise. 2D cultures are commonly used in a wide range of in vitro research studies, however, they do not resemble in vivo conditions, where cells would live and interact within a complex three-dimensional (3D) microenvironment. For this reason, 3D cultures were developed, so that they can provide a close representation or simulations of tissues in the living organism. Considering the mentioned approaches, we propose to develop a 3D model to generate the main two pathophysiological features of Alzheimer’s disease –plaques and tangles. The project aims to set a standard model to form plaques and tangles efficiently, and be able to target the aggregation of beta amyloids and tau proteins to prevent further aggregation in the future.​​​

BAS/1/1675-01-01

​Alzheimer’s, amyloids, disease model, neurodegenerative diseases

​Developing in vitro assays such as Thioflavin assay to follow up on plaque and tangle formation (Hauser), using selected short amyloid peptides to demonstrate amyloid formation (Hauser), study amyloidogenesis (Hauser,Michels), molecular dynamic computational simulations (Michels)

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

3D Bioprinting of Multicellular Constructs for the Development of Vascularized Skin Grafts

Academic Program: Computer Science

3D bioprinting technology has gained significant interest in biomedical engineering and regenerative medicine applications. However, current 3D bioprinting technologies utilize animal-based, plant-based, or synthetic polymer bioinks, which lowers biocompatibility with the patient. Additionally, the existing bioprinters use UV light or chemical treatment to polymerize the inks to form gels, which may cause unwanted mutations and faulty expressions of genes within the printed cells. The Laboratory for Nanomedicine at KAUST has developed a new technique which combines peptide-based bioinks and a robotic arm-based system for 3D bioprinting under true physiological conditions without any use of harsh physico-chemical methods. This project involves the development of vascularized skin grafts via 3D bioprinting of multicellular constructs for applications in the diabetic wound healing. Ultrashort peptide bioinks will be used as scaffolds for 3D bioprinting of human skin grafts.​​

BAS/1/1675-01-01

​3D bioprinting, biomedical engineering, tissue engineering, regenerative medicine, vascularized skin grafts

​Mastering 3D bioprinting using a commercial and a newly developed robotic 3D bioprinter (Hauser), Computational analysis of 3D bioprinting efficiency (Michels), creation of peptide bioinks (Hauser), developing skin grafts as a multicellular construct​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Inverse Problems in Imaging

Academic Program: Computer Science

Inverse problems are abundant in the field of imaging, and range from simple image processing tasks such as denoising and deblurring to full-scale reconstruction problems like computed tomography (reconstructing 3D volumes from 2D projections). The purpose of this internship is to learn about inverse problems, and critical techniques for solving them, including convex and non-convex optimization, sparse coding, and compressive sensing.​

BAS/1/2902-01-01

​Computer Science, Applied Mathematics.​

​This project requires some familiarity with basic numerical methods as well as programming skills. Close collaboration with other team members is expected. Possibility for co-authoring a scientific article in a conference or journal.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Computational Cameras

Academic Program: Computer Science

Computational cameras are imaging systems that are combinations of optics, electronics, and algorithms that jointly enable new approaches to image sensing. Computational imaging systems are of interest for applications such as polarization imaging, hyperspectral cameras, time-of-flight and depth imaging, light fields, high speed cameras, or cameras with small and exotic form factors. The internship will be to learn about computational imaging approaches, and work in an interdisciplinary team to develop new camera systems in one of the application domains.​

BAS/1/2902-01-01

​Computer Science, Electrical or Optical Engineering

​Depending on the background of the student, the work can be more optics oriented or more software oriented. Close collaboration with other team members is expected. Possibility for co-authoring a scientific article in a conference or journal.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

In-liquid Visualization of Phenol during Plasma Purification

Academic Program: Mechanical Engineering

In-liquid plasma generation is of interest topic due to intrinsic physics behind as well as a wide range of applications. This project consists of in-water electrical discharges with gas bubbles to investigate a degradation of phenol as a model contaminant. Particularly, a laser induced fluorescence will be adopted to visualize a spatial distribution of phenol when it is being decomposed.​​​

FCC/1/1975-06-01

​Mechanical Engineering

​Cross sectional imaging of phenol distribution with bubbles in water and Submission to a peer reviewed journal​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Molecular hospitality seen by NMR spectroscopy

Academic Program: BioScience

Supramolecular chemistry is the domain of chemistry beyond that of molecules that focuses on the chemical systems made up of a discrete number of assembled molecular subunits or components stabilized usually by weak interactions as van der Waals or electrostatic forces, or hydrogen bonding. Cyclodextrins (CD), one group of so called host molecules, are macrocyclic oligosaccharides composed of several glucosidic units. Other molecules called guests can enter their cavity forming inclusion complexes. In aqueous solutions, CDs can form guest/host inclusion complexes with many partially or fully lipophilic molecules. The inclusion CD complexes are widely used in modification of solubility and stability of pharmaceuticals, food and cosmetic additives, or enzyme simulation studies. Many physicochemical methods have been used to study the formation of weak inclusion complexes in solid and liquid states. There is no doubt that some methods are better suited to study such complexes than others, and among the nonseparation methods nuclear magnetic resonance spectroscopy is one of the most widely used because it delivers a wealth of highly reliable information at the atomic resolution level.​

BAS/1/1085-01-01

mariusz-jaremko@kaust.edu.sa

NMR

​chemistry, bioscience, physics, or engineering background

​Within the framework of the proposed project the participating student will learn about the supramolecular chemistry of cyclodextrin as well as extend own knowledge on the different host-guest interactions. The main method of the study of mentioned phenomena will be the Nuclear Magnetic Resonance (NMR) spectroscopy​

BioScience

Biological and Environmental Sciences and Engineering

Undergraduate

Deciphering the molecular mechanisms of DNA replication and repair – integration of computational and experimental approaches

Academic Program: BioScience

Genomic DNA is under constant assault by environmental factors that introduce variety of DNA lesions. The cell evolved several DNA repair and recombination mechanisms to remove these damages and ensure the integrity of the genomic DNA. These mechanisms use DNA structures that deviate from the heritable duplex DNA (flaps, nicks, gaps, bubbles and four-ways Holliday junctions) as common pathway intermediates. However, these structures are extremely toxic since they break the continuity of the heritable duplex DNA and impose impediment to replication and transcription. Members of 5’nuclease excise these aberrant DNA structures during replication, repair and recombination. It is not surprising therefore that mutations in members of 5’nucleases have been linked to various disease states including cancer and aging. Furthermore, some of these nucleases are highly over-expressed in several cancers to compensate for deficiencies in their damage response pathways.            Despite the importance of 5’nuclease it remains unclear how they recognize normal DNA sequence just based on their structure and precisely cleave them. The knowledge gap in structural studies that can access protein and DNA dynamics in 5’nucleases impairs substantially the drug development enterprises against numerous severe human cancers.            The proposed research project within the framework of the VSPR (Visiting Student Research Internship Program) program is mainly focused on the molecular bases of substrate recognition by 5’nucleases. The project combines cutting-edge computational resources and state-of-the-art biophysical computational tools, including full-atom molecular dynamics (MD) simulations, to establish the conformational states and dynamics of bubble DNA structure and how they are influenced by the bubble size and DNA sequence. DNA bubbles structure is the key intermediary step during nucleotide excision repair that separate the strand containing the lesion site from the intact one before two members of 5’nucleases, XPG and XPF, perform two concerted cleavages to release the damage-containing ssDNA. Establishing the bubble conformer(s) will pave the way for better understand of its interaction with XPG and XPF.            These studies will be accompanied and verified side-by-side by experimental results derived from the cutting-edge biophysical techniques, including single-molecule FRET (smFRET) and high-resolution multidimensional Nuclear Magnetic Resonance (NMR) experiments. In one alleged model, the bubble DNA structure might display dynamic conformations and the nucleases involved in NER simply capture the correct conformer. In another model the bubble might have stable conformer(s) and the nucleases actively bind to them and mold them into the ''correct'' conformer. The computational work, like full-atom molecular dynamics simulations assisted with the experiments smFRET and NMR data would help in decoding the actual mechanism of action of XPG and XPF against the bubble DNA.            This project is suitable for students with bioscience, physics, or engineering background.​​​

BAS/1/1085-01-01

​​ Structural Biology, Computational Biology, Protein-DNA interactions, FRET, NMR, Molecular Dynamics (MD), Biophysics

​We offer the students participating in this project to learn:how to use the biophysical techniques and design the workload;how to become self-reliant in the design, preparation, running and analysis of the molecular dynamics (MD) simulations of biologically essential macromolecular systems;how to analyze and integrate the results derived from different computational techniques with the experimentally derived information from the cutting-edge biophysical techniques, including smFRET and Bio-NMR.To complete the above tasks we expect from the students:A positive approach and strong will to work in the interdisciplinary and international research team;the preparation of the final report in the article format;the preparation of presentation that will be given during the group meeting.​

BioScience

Biological and Environmental Sciences and Engineering

Why it is so difficult to find potent drugs against cancer? - decoding the druggability of molecular targets

Academic Program: BioScience

The drug discovery process aims at finding novel, more potent small molecules (ligands) that can treat/cure certain human diseases, being a therapeutic agent, or serve in diagnosis of the early stages and progression of the disease. Despite the extensive joint efforts of many laboratories around the world, developing a potent drug is still a major and often a daunting challenge. As of now only 2% of human proteins interact with the currently approved drugs. On the top of that only 10% of human proteins are relevant to the disease. If a drug interacting with the target protein is known, and this interaction leads to therapeutic benefits of patients, then this target protein is called druggable. By simple approximation one can expect that other similar proteins, belonging to the same or related families, can be targeted by ligands - meaning: are druggable. Unfortunately it is often not a case, and only 10-15% of the human genome is predicted to be druggable, with only half of the targets being essential to any disease process.Our group is focused on understanding the molecular determinants driving the protein-protein and protein-ligand interactions, thus druggability of protein targets. We focus our attention on the closely related groups of proteins involved in the gene regulation processes, like histone methyltransferases and demethylases. These proteins covalently modify flexible tails of histones by attaching or removing the -CH3 groups to the side-chains of lysines and arginines. This way they modulate the accessibility of the DNA double strand - genes - toward transcription factor proteins and RNA polymerase. The miss-function of methyltransferases and demethylases is well known to lead to numerous severe cancers in human, like acute leukemia, variety of gastric carcinomas as well as several mental disorders, like schizophrenia.With the combination of molecular biology approaches we prepare and purify the human proteins of interest and subsequently study their structures and interactions with known drugs and other small molecules – ligands - potential candidates for becoming more potent drugs. In the lab we use multidisciplinary approaches and combine several state-of-the-art molecular biology and biophysical techniques. Our main technique, used and developed in the group, is the cutting-edge high-resolution nuclear magnetic resonance (NMR) spectroscopy. The conformational studies in solution are supplemented by other experimental biophysical methods, like X-ray crystallography, isothermal titration calorimetry (ITC), circular dichroism spectroscopy (CD), as well as advanced computational approaches - molecular dynamics (MD) simulations.In conclusion, with the combination of experimental and computational data for selected families of disease related proteins, we try to understand the molecular determinants that make closely related proteins druggable or not druggable.The proposed interdisciplinary project can host two VSRP students.The project offers the wide range of experience, from the protein biochemistry techniques that lead to preparation of biologically relevant material, followed by hands-on experience, i.e. from the design and performing the advanced nuclear magnetic resonance NMR experiments to preparation and running the comprehensive molecular dynamics MD simulations and finally integration of the results coming from the different fields of expertise.Students with the background in bioscience, physics and engineering, who enjoy working in the international and interdisciplinary environments, are welcomed to apply. ​​​

BAS/1/1084-01-01

​  bioscience, molecular biology, protein biochemistry, nucleic acids – DNA, computational structural biology, nuclear magnetic resonance NMR, epigenetics  ​

​We offer the students participating in this project to learn: •how to efficiently work in the state-of-the-art protein biochemistry lab, prepare own protein(s) for the biophysical and spectroscopic (e.g. NMR) studies and design the workload; •how to become self-reliant in the design, preparation, running and analysis of the advanced multidimensional NMR experiments, molecular dynamics (MD) simulations of biologically essential macromolecular systems; •how to analyze and integrate the results derived from different computational techniques with the experimentally derived information from the cutting-edge biophysical techniques, including Bio-NMR and X-ray. To complete the above tasks we expect from the students: • a positive approach and strong will to work in the interdisciplinary and international research team; •the preparation of the final report in the article format;•the preparation of presentation that will be given during the group meeting.

BioScience

Biological and Environmental Sciences and Engineering

Investigation of nanoparticulate morphology at PPC and HCCI modes

Academic Program: Mechanical Engineering

1. A thermophoretic probe will be designed for soot collection from engines exhaust pipe.2. The nanoparticulate will be collected for morphology from different combustion mode, like HCCI, PPC, and CI.3. The distribution of particle size and number density will be investigated.4. The low octane number fuel, naphtha, will be fueled with the compression ignition engine to investigate the nanoparticulate emissions​​​

BAS/1/1394-01-01

​Combustion engine and nanoparticulate emissions

​1.A thermophoretic probe. 2. Nanoparticulate TEM and HR-TEM images 2. 1-2 journal papers, like Combustion and Flame or Applied energy

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Development of algorithms to decipher the complexity of chromation organization

Academic Program: BioScience

Cells control gene expression by means of dynamic changes in chromatin. Different functional chromatin states are the result of highly combinatorial patterns of DNA- methylation, histone modifications, sequence specific DNA - binding proteins and chromatin accessory factors. The advent of large-scale, high- throughput experiments has resulted in the generation of an immense array of genome association data ( enrichment profiles) of chromatin components. Computational epigenetics is an interdisciplinary area of research that involves the development of computational methods to analyze and conceptionalize large scale epigenomic data.  At the Chromatin Biochemistry lab, we are developing computational methods for integrative analysis of Big-Data from ,odENCODE (1) to better understand the complexity of (epi) gennomic information. Decoding the increasingly large volumes of Bid-Data sets involves deciphering signal patterns and to systematically quantify the localization of these signal intensities.  ​​

ASP/1/1669-01-01

​computational biology, bioinformatics, informatics

​Develop (or assist/apply) computational method for segmentation of genomes using a combination of epigenomic datasetsApplication of machine learning techniques to predict the​ 3D architecture of epigenomic segments Maintain good log (CVS), submit progress in writing and present results Final report summarizing and explaining all project work. 

BioScience

Biological and Environmental Sciences and Engineering

Advanced Wastewater Treatment for Water Reclamation and Reuse

Academic Program: Environmental Science and Engineering

Wastewater is increasingly being viewed as an alternative non-conventional water source, accounting for a clear shift and changing paradigms in wastewater treatment and management. In this project, we aim to investigate and develop cost-efficient and sustainable treatment concepts that enable the use of treated wastewater for reuse purpose. The project will be focused on the recovery of nutrients from the treated wastewater and the removal of undesirable contaminants.

BAS-1061-01-01

Luca Fortunato

Water Desalination

​Environmental science and engineering

The student will learn various techniques to characterize the quality of water and food. He/She will learn different techniques necessary to monitor the efficiency of the process. Part of the work will be focused on the evaluation of different approaches for improving the quality of the treated water.

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Graduate

Water Desalination and Reuse Center

Fouling in Membrane Filtration Systems

Academic Program: Earth Science and Engineering

In the last decades the use of membrane systems for fresh water production has increased strongly to supply the growing water demand due to increasing human population, industrial and agricultural activity, economic growth and urbanization. Fouling represent one of the major drawbacks of membrane systems. In this project, we aim to explore different techniques in order to study the fouling developed in the system and relate with the membrane performance decrease. ​

ASP/1/1669-01-01

​Environmental science and engineering

​The student will learn various approaches to characterize the fouling developed in membrane filtration systems. He/She will learn different techniques (i.e. Confocal, Flow Cytometry, ATP, SEM, LCOCD etc). Several experiments will be run in order to relate the fouling developed in the system with the overall performance.

Earth Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Modeling structure and properties of transition metal complexes

Academic Program: Chemical Science

This project is focused on the characterization of transition metal based catalysts using quantum mechanics approaches. The applicant will have to correlate the experimental behavior of families of catalysts based on a transition metal to the structure of the ligand coordinated to the metal using molecular descriptors.​​​

BAS/1/1335-01-01

​Computational chemistry; catalysis.

​A scientific report summarizing the results of the research​

Chemical Science

Physical Sciences and Engineering

KAUST Catalysis Center

Complex optoelectronics materials and phenomena

Academic Program: Electrical Engineering

Design, fabrication and characterization of new complex materials and phenomena for different optoelectronics applications​. ​​

BAS/1/1628-01-01

​Physics or Engineering or Chemistry

​Learning of different nanofabrication techniques; assembly of complex materials​ structures for different photonics applications

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Cutting-edge research on materials, devices, or physics of the third-generation semiconductor

Academic Program: Electrical Engineering

The wide bandgap semiconductors, also known as the third-generation semiconductors, have enormous potentials to revolutionize almost every industry on the planet and in space. Because of the unique and superior properties, they can be made in ultra-efficient, ultra-sensitive and ultra-reliable optical and electronic devices. Despite being in the early phrase of development and commercialization, the third-generation semiconductors have already resulted in industries worth of hundreds of billions USD and creating numerous jobs, as well as 2014 Nobel Prize in Physics. Opening your phone, computers and anything using electricity, you will likely find plenty of them. More potentials are to be unlocked by smart and hard-working researchers such as you. This VSRP project is offered by the Advanced Semiconductor Laboratory, a world-leading laboratory with state-of-the-art facilities in the third-generation semiconductor research. The VSRP students will have the opportunity to learn the latest materials, devices, and physics of the third-generation semiconductor as well as the combination with other exciting things such as 2D materials and quantum photonics. More importantly, every VSRP student will have his/her own project to solve a key problem. The project needs 4-6 months to be completed. It is going to be an exciting period with intense training and research work both theoretically and experimentally. Successful students can likely publish their results in prestigious scientific venues. ​ ​​​​​​​

BAS/1/1664-01-01

​Electrical/Electronic Engineering, Physics, Material Science, Chemistry

​In research, no deliverables can be compared with a patent or a peer-review paper. In the past, all the VSRP students can generate patents or publish first-authored or co-authored papers in prestigious journals. The publication record has help strengthened their credentials greatly for future career development. Therefore, the incoming VSRP students are expected to do the same. PS: one example can be found here: https://goo.gl/8sorGf​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Plant-Beneficial Microbe Interaction

Academic Program: BioScience

Abiotic stresses are the most important factors for hampering plant growth and yield world-wide. However, beneficial microbes can help plants to enhance stress tolerance of plants. DARWIN 21 is a large scale project to isolate and study the interaction how rhizophere microbes contribute to enhance the capacity of plants under the most difficult abiotic stress conditions (http://www.darwin21.net/index.htm).In this project, the student will characterize several rhizosphere microbes and investigate whether they can confer plant resistance to different abiotic stresses. The student will learn how to apply techniques in microbiology, molecular biology and plant biology.​​

ASP/1/1669-01-01

​Microbiology, Genomics, Plant biology, Bioinformatics

​Isolation and characterization of bacterial strains. Analysis of beneficial microbes on plant physiology. Sequencing and bioinformatics to analyze microbial genomes, transcriptome and proteome analysis of beneficial microbes and plants.

BioScience

Biological and Environmental Sciences and Engineering

Center for Desert Agriculture

Cutting-edge genomics to unravel the genetic basis of disease resistance in crop plants 2

Academic Program: Plant Science

A significant proportion of the global crop harvest is lost to diseases each year. A better understanding of the genetic and molecular components that control disease resistance in crop plants is thus of paramount importance to breed the cultivars capable of feeding 9-10 billion people by 2050. The isolation of disease resistance genes from the important cereal crop plants wheat and barley is very challenging because these two crop species have very large and complex genomes. Our group has developed novel and rapid gene cloning approaches that combine the latest developments in genomics, molecular biology and bioinformatics. This internship offers the possibility to learn these novel approaches and to be actively involved in a hands-on gene cloning project.​

BAS/1/1082‐01‐01

​Crop Genetics

​Training in crop genomics, bioinformatics, phytopathology, and molecular biology​ 

Plant Science

Biological and Environmental Sciences and Engineering

Cutting-edge genomics to unravel the genetic basis of disease resistance in crop plants

Academic Program: BioScience

A significant proportion of the global crop harvest is lost to diseases each year. A better understanding of the genetic and molecular components that control disease resistance in crop plants is thus of paramount importance to breed the cultivars capable of feeding 9-10 billion people by 2050.The isolation of disease resistance genes from the important cereal crop plants wheat and barley is very challenging because these two crop species have very large and complex genomes. Our group has developed novel and rapid gene cloning approaches that combine the latest developments in genomics, molecular biology and bioinformatics.This internship offers the possibility to learn these novel approaches and to be actively involved in a hands-on gene cloning project.

BAS/1/1082‐01‐01

Crop genetics

​Training in crop genomics, bioinformatics, phytopathology, and molecular biology​ 

BioScience

Biological and Environmental Sciences and Engineering

Identifying the genetic drivers of thermal tolerance plasticity in the coral model Exaiptasia

Academic Program: Marine Science

The objective of this project is to identify the genetic drivers of thermal tolerance plasticity in the coral model Exaiptasia pallida. To achieve this goal the organism will be subjected to thermal stress over a period of time, sampled at many time points, RNA extracted, sequenced and analyzed for gene regulatory networks. Outcomes of our research has multiple benefits. Our results will lead to (but not limited to) enrichment of knowledge base of coral community, identification of new candidate genes for further functional genomic studies and reconstruction of gene regulatory networks.  Recommended Student Academic & Research Background:Molecular biology with wet lab experience, undergraduate or postgraduate in biotechnology/biology/molecular biology ​ ​

BAS/1/1036-01-01

​Marine Molecular Ecology ​

The project is multi-disciplinary in nature and requires wet-lab (80%) [and | or] soft-skills (20%). Soft-skills though not mandatory can be learnt during the course of project upon his/her initiative. The deliverables for the project are: 1) Regular plan for growth and proliferation of sea anemones 2) Setting up time series experiment 3) Optimize existing protocols to maximize the yields of nucleic acid (RNA/DNA) 4) Basic data analysis of RNASeq data 5) Consolidated report at the end of internship The expectations from the intern are his/her experiences in: 1) Basic wet laboratory skills 2) Animal care procedures 3) Molecular biology techniques – RNA isolation, DNA isolation 4) Knowledge on basic UNIX and soft skills (added advantage) In general, the intern is expected to be pro-active with eagerness for broadening his interests and meet PI at least once in 2 weeks to discuss about the progress of the research.​

Marine Science

Biological and Environmental Sciences and Engineering

Red Sea Research Center

Improving coral thermal tolerance through association with acclimatized Symbionts

Academic Program: Marine Science

Corals have shown capable of coping with increasing temperatures; however strong inter-species and intra-species variation is evident. Different thermal tolerances between members of the same species have been attributed partially to the associated zooxanthellae. The Red Sea offers a unique environment to understand these associations as host and symbiont live in higher annual temperatures than counterparts elsewhere. Using the coral model organism Aiptasia pallida, a small anemone, we investigate whether Symbiodinium from anemones of the Red Sea can improve heat stress resilience of individuals from geographically distant locations. ​​

ASP/1/1669-01-01

​Biological Sciences, Marine Sciences

 Bleaching and re-infecting anemones with different strains of Symbiodinium cultured in the labQuantification of phenotypic changes between host-symbiont combinations during and after heat stress exposure RNA extraction and gene expression analysis of interesting and informative biomarkers Perform further analysis on data obtained Write a (short) manuscript of these analyses​

Marine Science

Biological and Environmental Sciences and Engineering

Red Sea Research Center

High resolution remote sensing of agricultural systems for improved water and food security

Academic Program: Environmental Science and Engineering

A range of high-resolution (1-10m) space based commercial systems have recently become available for earth observation. There is considerable capacity to develop products on various terrestrial surface features from these, including vegetation health and stress, land cover changes and even digital surface models. Here we will explore some of these opportunities using high-resolution commercial as well as government based satellite systems, with a focus on applications in precision agriculture.​​

ASP/1/1669-01-01

​Computer science, civil and environmental engineering, statistics, applied math

​Skill development in programming (Python, Matlab); analysis and interpretation of high-resolution satellite imagery; derivation of geospatial data sets for food and water security assessment; knowledge development related to remote sensing, water resources, agricultural systems, machine learning and big data analysis. 

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Polymeric membranes for liquid separation

Academic Program: Environmental Science and Engineering

Development of polymeric membranes for different separations, aiming at applications in the chemical industry or water treatment. The project will involve polymer modification or crosslinking, morphology control and characterization, and filtration performance evaluation.  ​

ASP/1/1669-01-01

​Chemistry, chemical engineering, polymer science​

​Membranes with controlled porosity and different chemical functionalizations Morphology imaging (electron microscopy)

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

An iPSCs-based approach to model Type Two Diabetes in-vitro

Academic Program: BioScience

Studying the transcriptional and epigenetic mechanisms dysregulated in patients affected by metabolic disorders such as insulin resistance (IR) and type 2 diabetes mellitus (T2DM) is essential to derive efficient pharmacological approaches. We are seeking an outstanding student to work on a project focused on the study of the role of histone modifiers to the onset of metabolic disorders.​​​​​​

BAS/1/1077-01-01

​Molecular and Cellular Biology and/or Bioinformatics

​The selected candidate will use human stem cells and terminally differentiated glucose sensitive cell types and will acquire skills in molecular biology techniques including Chromatin Immuno-precipitation (ChIP), quantitative real-time PCR (Q-PCR) and next generation sequencing (NGS).​

BioScience

Biological and Environmental Sciences and Engineering

Large-scale scholarly data mining

Academic Program: Computer Science

Delve is an on-going project in my group. It is a web-based dataset retrieval and document analysis system. Unlike traditional academic search engines (e.g., Google Scholar) and dataset repositories (UCI repository), Delve is dataset driven and provides a medium for dataset retrieval based on the suitability or usage in a given field. It also visualizes dataset and document citation relationship, and enables users to analyze a scientific document by uploading its full PDF.​​​​

BAS/1/1635-01-01

​Machine learning, data mining

​The internship position is for candidates who can contribute to the system by using machine learning and data mining techniques on the analysis of document text, citation and co-author graphs. Deep learning, graph embedding and graph mining techniques should be explored for improving the search accuracy in the system.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Anaerobic membrane bioreactor as a decentralized municipal wastewater treatment technology

Academic Program: Environmental Science and Engineering

This project looks into scaling up anaerobic membrane bioreactors to treat municipal wastewaters. A pilot-scale anaerobic membrane bioreactor will be constructed and operated to treat municipal wastewater. Reactor performance will be evaluated along with the effluent quality. ​

ASP/1/1669-01-01

​Chemical or Process Engineering ​

​The deliverables are to come up with a process reactor design for the scaled-up anaerobic membrane bioreactor; a lab-scale anaerobic membrane bioreactor will be operated to treat municipal wastewater; reactor performance will be assessed; effluent quality will be measured; effluent will be used to irrigate agricultural crops; crop yield and health will also be evaluated in collaboration with Professor Ikram Blilou’s group. 

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Screening for Carotenoid-Derived Signaling Molecules

Academic Program: BioScience

The project focuses on novel signaling molecules involved in plant development and response to environmental stress. It includes studies on the activity of selected carotenoid-metabolizing enzymes and the identification of their enzymatic products. Biological activity of products will be investigated by developmental assays using Arabidopsis and rice and by determining the effect of these compounds on the transcript levels of selected genes including strigolactone biosynthesis genes. These studies will be complemented by geno- and phenotyping of mutants disrupted in the corresponding genes. ​

ASP/1/1669-01-01

​Plant Biochemistry and Development

​Identification of new bioactive compounds/Better understanding of the regulation of strigolactone biosynthesis. Significant contribution to a publication 

BioScience

Biological and Environmental Sciences and Engineering

Center for Desert Agriculture

Protein Synthetic Biology

Academic Program: BioScience

The student will work in the synthetic biology team of the Stefan Aroldlabin KAUST. The team is focusing on the design of multi-protein systems such as protein circuits or small metabolic pathways. We can offer both experimental (biophysical, molecular biology, automation) and computational or software development projects or a mix of the two.Experimental work would deal with the construction of small metabolic pathways or multi-protein circuits and their rapid prototyping in a cell-free expression system. We have started to combine this cell-free expression with microfluidics and are also actively developing automation workflows on the lab's liquid-handling robots. Software development projects would aim for improving biodesign and engineering workflows together with the experimentalists in the lab.​ ​

BAS/1/1056-01-01

​Synthetic Biology (experimental, computational)

​Exact deliverables depend on the type of work (experimental and / or computational). Experimental deliverables could be, for example, the expression and detection of a set of target proteins in microfluidic droplets or the automation of a cloning or protein expression experiment on a liquid handling robot. Software development would build on existing Python libraries to streamline biodesign workflows in the lab (e.g. multi-domain protein design).​

BioScience

Biological and Environmental Sciences and Engineering

Computational Bioscience Research Center

Structural Landscape of Genetic Diseases

Academic Program: BioScience

Advances in gene sequencing have led to the production of a wealth of data linking gene mutations to patient phenotypes. Structural biology can often reveal the underlying molecular basis of a particular protein mutation but existing tools only look at one gene at the time. This project aims at producing a software tool that allows performing this structure-function analysis on a large scale and thus to analyze structural mechanisms of diseases from big data resources.​

ASP/1/1669-01-01

​  Computer science, bioinformatics  ​

​Creation of several modules to compute/retrieve sequence-and structure-based properties and integrate them in 3D (structure) space;  Conversion and cleanup of high-quality human mutation data from clinical collaborator; Integration and correlation of both.

BioScience

Biological and Environmental Sciences and Engineering

Computational Bioscience Research Center

Structural Biology of Immune Signalling

Academic Program: BioScience

In the Arold lab, we use biochemistry, biophysics and structural methods such as X-ray crystallography, small angle X-ray scattering, nuclear magnetic resonance and cryo-electron microscopy to reveal the 3D structure of protein complexes involved in controlling the immune system. The student will be embedded in a team of structural biologists and help with protein production and biochemistry, crystallization screens and EM particle picking. Some prior wet-lab experience would be a plus.​​

ASP/1/1669-01-01

​Computer science, bioinformatics

​​Recombinant production and purification of proteins. Biophysical protein assays. Structure determination of proteins or protein-ligand complexes.

BioScience

Biological and Environmental Sciences and Engineering

Computational Bioscience Research Center

Simultaneous Communications and Localization Low Data Rate Low Cost Sensing Systems

Academic Program: Electrical Engineering

The aim of the project is to design and study the performance of asystemthatcan combine communications andlocalization.The envisionedapplicationscenario is for low cost sensors where adding extra hardware andprocessingpower to aid in localization is notdesirable.In short, the idea is todesigna "cheap" sensor that can utilize the same HW to send the data it collects and allow other devices to determine its position.

BAS/1/1665-01-01

​Electrical Engineering

​​1) Designing singaling schemes for joint communication and localization2) System implementation using MATLAB and/or low level embedded system programming 3) Testing the system performance in a controlled environment

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

GNSS attitude determination and precise positioning

Academic Program: Electrical Engineering

The goal of this project is to develop new techniques for accurate GPS/GNSS positioning and attitude determination for mobile platforms (vehicles, etc.). The main application area is vehicle control and vehicle autonomy. The project focuses on instantaneous methods that are capable of delivering real-time results in semi-occluded environments such as urban areas. This requires extending existing techniques of phase ambiguity resolution, or developing new methods. Methods that leverage multiple GNSS signals (from GPS, GLONASS, etc.) will be given more consideration. A GNSS testbed is available in lab that will be used to carry out the experimental part of this project.This project consists of different activities: 1. Review relevant and most recent publications in the area.2. Develop the precise positioning and/or attitude determination techniques from first principles or by extending existing methods.   3. Study the performance of the developed methods using simulations.4. Carry out experimental tests using the existing GNSS testbed.5. Analyze the results and derive conclusions. Write final report.6. Write publications and attend relevant conferences/events to gain more knowledge in the area.​ ​​​

BAS/1/1637-01-01

​Electrical Engineering

​1. A complete assembled system (hardware + software).2. Final design, algorithms and system parameters. 3. Experimental results.   4. Final report summarizing and explaining the whole project with results and future recommendations. 

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Cutting-edge red light- emitting diodes by nitride semiconductors

Academic Program: Electrical Engineering

Nitride semiconductors are an excellent candidate for light-emitting devices because they canmakeallvisiblelights.Inprinciple,itispossibletosimultaneouslyfabricatetheLEDsof Red-Green-Blue primary colors, for instance, it is expected that micro-LED chips capable of displaying high contrast and full color indicating can be manufactured at lower cost. The micro-LED displays are expected as the next-generation after the OLED displays. However, it is well known that the nitride semiconductor red LEDs are quite challenging to develop. Our group found out the break-through to create the red LEDs and leads the research on it in theworld.The following topics are available for internship students.1.Opto-electricalcharacterizations2.DevicesimulationThe students will learn the various characteristics such as SEM, XRD, PL, AFM and so on. This project needs 3-6 months to be completed​

ASP/1/1669-01-01

​Electrical Engineering, Applied Physics

​The internship students will learn the opto-electrical knowledge through the development of red-LEDs by nitride semiconductorsThe students are expected to work full-time. The results are utilized for publications. The students attend weekly meetings with the Faculty Advisor

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Water splitting to produce clean hydrogen energy by semiconductor band engineering

Academic Program: Electrical Engineering

To suppress or recover from the global warming, development of clean energy technology is important to research area from now on. Hydrogen is useful energy for fuel-cell cars, aircraft, etc. Since hydrogen becomes water after its combustion, it is clean energy. If hydrogen gas could be produced from natural energy such as solar light, the final clean energy cycle would be possible.Let’s develop clean energy technology together. The following topics are available for internship students.1.Photocatalysis for hydrogen generation2.Co-catalyst study for higher efficiency3.Other state-of-art topics​The students will learn and challenge electrochemical measurement, photocatalytic measurement, and various physical & chemical characterization such as SEM, Spectroscopy, XRD, XPS, gas/liquid/ion chromatography. This project needs 2-6 months to be completed. ​​​​

BAS/1/1676-01-01

​      Chemistry, Physics, and Electrical Engineering

​The internship students will learn photo-electrochemical knowledge on energy conversion by semiconductors from light to hydrogen clean energy. The students are expected to work full-time. The results are utilized for publications. The students attend weekly meetings with the Faculty Advisor​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Making ML-based Networked Systems more Trustworthy

Academic Program: Computer Science

​Machine learning (ML) solutions to challenging networked systems problems are a promising avenue but the lack of interpretability and behavioral uncertainty affect trust and hinder adoption. The goal of this work is to develop new solutions to facilitate the training of robust ML-based decision-making agents for systems. With their recent advancements, today’s ML solutions provide remarkable results in many fields. ML methods have been recently applied to several networked systems problems including routing, congestion control, resource allocation, flow scheduling and video rate adaptation. In particular, Reinforcement Learning (RL) has been a main approach due to its ability to directly learn from experience and simulation without relying on labeled datasets, and to optimize any desirable metric. Yet, there is a general fear that ML systems are black boxes: closed systems that receive an input, produce an output, and offer no clue why. This creates uncertainty about why these systems work, whether they will continue to work in conditions that are different from those seen during training or whether they will fall off performance cliffs. Given their statistical nature, it is difficult to predict how ML-based agents will behave when faced with previously unseen inputs. Because of this uncertainty, it is not possible to let these agents control critical, large scale systems without safety guarantees, despite the evidence that ML solutions can yield better efficiency and resource utilization than classical approaches. We seek to address this problem.​​​​​

ASP/1/1669-01-01

​Computer Science​

​The goal of this internship is to verify and improve existing ML agents. The student will be expected to learn about existing solutions, as well as the challenges and requirements to applying ML techniques in their settings. With guidance of other team members, the student will then find new solutions for either verifying the safety of ML agents or improve their behavior in order to reduce risks related to the safety and stability of the agent’s decisions. Possible directions include (1) analyzing the agent behavior based on symbolic or concolic execution, (2) exploring the evolution of the agent’s behavior during training, (3) considering new ways of modifying a trained agent to meet stricter requirements. Candidates should be motivated to work on research-oriented problems with a team and develop new solutions in a budding field. They should have a strong background in computing and software engineering, in particular with regards to machine learning, networking, and distributed systems. Ideally, they should have experience in building machine learning solutions and working with related tools, as well as knowledge of Python​.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

High-efficiency AI and ML distributed systems at Big-Learning scales

Academic Program: Computer Science

The position will be in the context of a project whose goal is to make distributed AI and ML more efficient. Enabled by the rise of big data, today’s AI and ML solutions are obtaining remarkable success in many fields thanks to their ability to learn complex models with millions to billions of parameters. However, these solutions are expensive because running AI and ML algorithms at large scales requires clusters with tens or hundreds of machines to satisfy the high computation and communication costs of these algorithms.Many systems exist for performing AI and ML tasks in a distributed environment. Yet, the performance requirements and input data sizes are steadily growing. The next level of efficiency is required to address key challenges like network communication bottlenecks and uneven cluster performance.Moreover, the fidelity of ML models is very sensitive to many hyperparameters. To produce accurate models, it is of great importance to tune these hyperparameters well. However, this requires exploring a large space of possible configurations, which must be done efficiently. The internship work will generally integrate in the current challenges faced during the project whether that is to investigate the trade-offs between reduced communication and model precision or to identify the bottlenecks and develop new algorithms to overcome them.Ongoing directions are (1) exploring the use of new networking hardware and architectures to make network-based communication more efficient and (2) designing new search algorithms that can make a better use of resources and determine optimized hyperparameters more efficiently.Candidates should be motivated to work on research-oriented problems in a fast-paced and tight-knit team. They should have a strong computing or engineering background with a good background in algorithms, machine learning, distributed systems, and networking. Ideally, they would have experience in building and working with large software systems and tools, and proven knowledge of C++/Java.​​​​

BAS/1/1673-01-01

​Computer Science

​The students are expected to study the existing solutions and devise theoretically-sound approaches (with the assistance of the supervisor) to improve their performance. The students will be able to also collaborate with other team members and to evaluate the mechanisms on real-world datasets on a state-of-the-art testbed. The above results, if completed, are considered novel and can result into a publication (with the agreement of the supervisor). ​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Machine Learning for Graphs

Academic Program: Computer Science

We have numerous projects where we work networks or graphs of various kinds, biological ones in particular. Networks can be undirected, directed with or without signs, discrete or continuous.

For publications see google scholar (https://scholar.google.com/citations hl=sv&user=_DUppAgAAAAJ&view_op=list_works&sortby=pubdate).

Challenges and sub-projects include:-         

How to compare 2 and several networks,review,benchmark current methods, invent new efficient algorithms for network comparison

-Analyze networks embedded in hyperbolicspace

-Review, benchmark current methods for embedding networks into anML framework

-Generative modeling of networks constrained by correlational information from data-sets

-Partially overlapping networks,analyzetheirputativealignment,constructionof multi-layer networks from several partially overlappinggraphs.

-Search and propagation in multi-layernetworks

-Alignment of several but different real protein interaction networks​

ASP/1/1669-01-01

jesper.tegner@kaust.edu.sa

LivingSystems

​Computer Science, Applied Mathematics

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. We expect you (a) to bring enthusiasm, creativity, and hard work, (b) give lab seminars on your work, and (c) produce a final written report.In returnthis facilitates your critical thinking, presentations skills, and scientific writing.Yourresearch, in collaboration and with support of team members, may lead to scientific publications. You will also get a good hands-on perspective at the frontier of machine intelligence and its applications in an interdisciplinary research group andenvironment.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Machine Learning for Biological and Medical Imaging

Academic Program: Computer Science

We have recently developed hybrid machine learning techniques for retinal images. For publications see google scholar(https://scholar.google.com/citations?hl=sv&user=_DUppAgAAAAJ&view_op=list_works&sortby=pubdate). Challenges include limited number of images, unbalanced data-sets, and interpretability of feature representations. Subprojects include to

Formulation and training of robust generative models (e.g.GANsand versions thereof) for the Retinal Dataset-

Extend and apply the techniques to melanoma datasets Develop and apply techniques to identify meaningful (biological/medical) feature representation from a successfulclassification

ASP/1/1669-01-01

jesper

bio

​Computer Science, Applied Mathematics

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. We expect you(a)tobringenthusiasm,creativity,andhardwork,(b)givelabseminarsonyourwork, and (c) produce a final written report.In returnthis facilitates your critical thinking, presentations skills, and scientific writing.Yourresearch, in collaboration and with support of team members, may lead to scientific publications. You will also get a good hands-on perspective at the frontier of machine intelligence and its applications in an interdisciplinary research group andenvironment​.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Graduate

Algorithmic Information Theory for Machine Intelligence

Academic Program: Computer Science

We recently developed numerical and computational techniques to use algorithmic information theory (AIT) to the analysis of networks. For publications see google scholar(https://scholar.google.com/citations?hl=sv&user=_DUppAgAAAAJ&view_op=list_works&sortby=pubdate).Subprojects include to-         Develop python packages for AIT analysis of large-scalenetworks-         Develop new AIT network embedding algorithms-         Analyze Convolutional Networks a representational learning usingAIT-         Quantify and benchmark AIT network analysis with othertechniques-         Large-scale computation of AIT networks using a supercomputer(Shaheen)Newand improved numerical approximation of algorithmic complexity using massive computations of Turing Machines on Shaheen(supercomputer)

ASP/1/1669-01-01

​Computer Science, Applied Mathematics

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. We expect you (a) to bring enthusiasm, creativity, and hard work, (b) give lab seminars on your work, and (c) produce a final written report. In return this facilitates your critical thinking, presentations skills, and scientific writing. Your research, in collaboration and with support of team members, may lead to scientific publications. You will also get a good hands-on perspective at the frontier of machine intelligence and its applications in an interdisciplinary research group and environment.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Learning Generative Causal Models from Sparse Temporal Observations during Cellular Reprogramming

Academic Program: BioScience

​Recent work on stem cells and different mature specialized cells in different systems/organs (neurons, blood cells,) has revealed a stunning plasticity and capacity of reprogramming cells. For example, mature cells can be reprogrammed into pluripotent stem cells, and exciting work on engineered design of tissues and organs (organoids) are underway. On the one hand the community has since the sequencing of the human genome produced very efficient tools to read off the corresponding molecular events accompanying reprogramming and engineering of cells. Recently, the discovery of the CRISPR techniques has equipped us with unprecedented opportunities for precise writing or editing of the genomes. These developments in fundamental biology and biotechnology are currently opening new tools and perspectives of vital significance for drug development, regenerative medicine, synthetic biology, and personalized medicine. Yet, in essence all these efforts require and would be greatly facilitated if we could advance from correlative data-analysis to a predictive discovery of which interventions (edits, engineering) are producing which effects. Thus, we are facing the fundamental problem on how to discover causal relations from data, or in other words, can we derive quantitative predictive laws fromdata?We offer internships forseveral highly motivatedbachelor (B.Sc.) ormaster (M.Sc.) students who will explore this fundamental question primarily from a computational standpoint. This includes using high-performance simulations of dynamical models, and design of algorithms in a controlled in-silico environment. For example, to identify (a) efficient algorithms for generation of ensembles of dynamical models, (b) use supervised deep learning algorithms for pattern discovery in large-scale simulation data-sets, (c) to perform deep data-driven analysis of computational models in biology, (d) pursue investigations of transfer entropy and related techniques for system identification. These tools will be tested utilizing rich and recent molecular data on cellular reprogramming.​​ ​​​​

BAS/1/1078-01-01

​computer science, mathematical modeling, machine learning, systems biology, bioscience

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. The project is suitable for candidates fascinated by dynamical causal systems, be it computational or those we find in the natural world, i.e. living cells. We expect you (a) to bring enthusiasm, creativity, and hard work, (b) give lab seminars on your work, and (c) produce a final written report.In returnthis facilitates your critical thinking, presentations skills, and scientific writing.Yourresearch, in collaboration and with support of team members, may lead to scientific publications. We publish avidly in both bioscience and computational sciences, not for the fame but rather as steps aiming to and motivated both by our quest of asking fundamental questions of relevance to human nature and discovery of transformative intelligent technologies inspired from nature. You will get a good hands-on perspective on the frontiers in dynamical systems and bioscience using state-of-the-art simulation and machine learning tools.

BioScience

Biological and Environmental Sciences and Engineering

Deep Learning and Machine Intelligence for Single Cell Genomics

Academic Program: BioScience

Single cell biology and genomics in particular are currently transforming the biosciences. Single cell RNA sequencing (scRNAseq), method of the year 2013 (Nature Methods), has now matured and large amounts of scRNAseq are now available. These data, characterizing living systems at an unprecedented level of resolution, hold the promise to set the stage for a fundamental quantitative understanding of living systems with special reference to genomic regulation and collective computation. Yet, there are a number of open problems on how to think about these data and how to pragmatically analyze them.In parallel, we have witnessed a rapid development in machine learning. The rise of computation, such as supercomputers (shaheen@KAUST) and GPU based techniques, in conjunction with data explosion (often referred to as big data), has fuelled the development of new techniques aiming for machine intelligence. In particular, techniques inspired from livings systems, such as deep convolutional networks, currently experience a renaissance. Driving forces include not only data and computation but also the availability of suite of open source platforms (e.g. Theano, Caffe, Torch7, TensorFlow) supporting machine-learning algorithms. These algorithms represent industry standard for processing images, speech, text, and runs on the majority of services and devices provided by Google, Amazon, Facebook, to name a few big players, as well as a numerous startups.We offer internships for several highly motivated bachelor (B.Sc.) or master (M.Sc.) students who will identify (a) appropriate supervised deep learning architectures and training algorithms for scRNAseq data, (b) explore generative adversarial network (GANs) techniques for estimation of high-dimensional data distribution in the single cell gene expression space. This work will be used to develop new techniques and to address open problems in single cell genomics such as pseudo-temporal ordering of single cell data, clustering of data, investigate representations, transfer learning, and unsupervised feature discovery. ​​​

BAS/1/1078-01-01

​computer science, bioscience, machine learning, systems biology, artificial intelligence​

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. The project is suitable for candidates fascinated of living systems, interested in cutting edge bioscience, and artificial intelligence for science and not for discovering cats in YouTube. We expect you (a) to bring enthusiasm, creativity, and hard work, (b) give lab seminars on your work, and (c) produce a final written report.In returnthis facilitates your critical thinking, presentations skills, and scientific writing.Yourresearch, in collaboration and with support of team members, may lead to scientific publications. We publish avidly in both bioscience and computational sciences, not for the fame but rather as steps aiming to and motivated both by our quest of asking fundamental questions of relevance to human nature and discovery of transformative intelligent technologies inspired from nature. You will also get a good hands-on perspective at the frontier of bioscience and machine intelligence in an interdisciplinary research group and environment.

BioScience

Biological and Environmental Sciences and Engineering

Visualization of time dependent oil displacement from core plugs by X-ray CT

Academic Program: Energy Resources and Petroleum Engineering

​The goal of the project is to develop a procedure for X-ray CT imagingofoil/water saturation in a carbonate core.​

BAS/1/1378-01-01

​Petroleum Engineering, Mechanical Engineering, Chemistry, Physics

​Final report (in English) summarizing work results, sample prep, image acquisition procedure, and other outcomes and their discussion. Documented code for image analysis routine. Presentation of the results on a group seminar.

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Visualization of Oil Displacement Patterns in Micromodels

Academic Program: Energy Resources and Petroleum Engineering

The goal of the project is to test and establish procedures for saturation and flow visualization in custom-made micromodels.

BAS/1/1378-01-01

​Mechanical Engineering, Materials Engineering, Chemical Engineering

​Participate in micromodel fabricationMake significant contribution to micromodel initialization protocol  Explore available micromodel visualization approaches Write a complete report Present results on a group seminar​

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Numerical modelling of capillary driven flow using OpenFOAM

Academic Program: Energy Resources and Petroleum Engineering

Work on running simulation of multi-phase capillary driven flow inchannelsof different geometries and wettability properties. Study numerically the effect of dynamic contact angle on capillary driven flow.

BAS/1/1378-01-01

​Fluid dynamics modelling

​Work on improving the accuracy/sharpness of the fluids interface using OpenFOAM multiphase flow solversIncorporate the dynamic contact angle into multiphase flow Benchmark the numerical simulation against available analytical solutions and experimental data Write complete report, provide documented code/input files to OpenFOAM, present results on group seminar.​​

Energy Resources and Petroleum Engineering

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Big Data: Mess versus Value

Academic Program: Chemical Science

The problem of “messy” drilling and downhole data, and how to extract maximum value from it, is a pertinent challenge for the petroleum industry – in particular when it comes to advancing the understanding of near‐wellbore physics and chemistry. This is particularly important since technological advancements, workflow optimizations and integrated project processes/execution are directly linked to a reduction in the cost of well construction, which generally is the largest expenditure item during field development. We are looking for a highly motivated bachelor or master student who will be responsible for​ loading, processing, and analyzing continuous data streams from wellbores acquired with sensors during the drilling and reservoir monitoring process (e.g., measurement or logging while drilling). The purpose is to find in and extract from these data key information necessary to optimize drilling and improve our understanding of the processes ongoing in the near wellbore region.Results from this internship project will be integrated into the development of automation systems that are capable of handling massive data streams from drill sites, maximize the quality of these data streams, find key information necessary to optimize drilling (i.e., lower cost), and help reduce risk, lost and non‐productive time (i.e., prevent failures and accidents).We expect that this research will lead to publications, which the student can contribute to. ​​​​

BAS/1/1378‐01‐01

Drilling, production, or reservoir engineering.

​We are seeking a B.Sc. (Bachelor of Science) or M.Sc. (Master of Sciences) student who is interested in the stated topic for his / her thesis research. The project is suitable for candidates interested in rock mechanics, geo‐chemistry, or/and data analysis / statistics.​

Chemical Science

Physical Sciences and Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Development of Electrochemical Sensors for Environmental Monitoring

Academic Program: Chemical Science

In many biological processes, the selective molecular recognition is considered as the key factor; since then, the basic principle and aim of molecularly imprinted polymers (MIPs) focused on the substitution of the natural receptors such as antibodies and enzymes by other biomimetic recognition elements based on synthetic receptors based on stable imprinted polymers.MIPs based electrochemical sensors showed various advantages from MIP films and the electrochemical transducers, which include high sensitivity and selectivity, high chemical/mechanical stability, facile preparation, miniaturization as well as their reusability. The highly mechanical/thermal stability, excellent selectivity and sensitivity of MIPs?based electrochemical sensors indicate a greater prospect for high?quality sensing applications, compared to the traditional instrument techniques and other types of sensors.Therefore, this research internship will focus on the development of low-cost, simple and rapid electrochemical sensors based on MIPs for environmental applications. Some knowledge of any of the following is preferable: Electrochemical detection, characterization of MIP based sensors using SEM/TEM, FT-IR, XRD, RAMAN, AFM, Real samples preparation, Validation of the electroanalytical methodPreferred background: Chemistry, Materials science ​

BAS/1/1605-01-01

​Chemistry, Materials science

​Objectives:•     Development of a sensitive, selective electrochemical sensor basedonMIPs •     Morphology and structural characterization of the MIP based sensors •     Application for environmental monitoring  Tools to learn: Electrochemical detection, characterization of MIP based sensors using SEM/TEM, FT-IR, XRD, RAMAN, AFM, Real samples preparation, Validation of the electroanalytical method

Chemical Science

Physical Sciences and Engineering

Fano Resonant Gas Sensors

Academic Program: Electrical Engineering

One of the most important global issues as classified by the United Nations is related to health. And one way to help mitigating this concern consists in developing precise and low cost sensors for toxic gas to avoid contamination and help in saving human lives. In this vein, the demand of the gas sensors is increasing in the fields of environmental monitoring, oil and gas, automotive, building safety, and also in the house hold consumer market. A fresh approach is therefore imminent to design low cost, efficient and sensitive gas detection systems. In this internship, we propose a new class of the nano-particle impregnated integrated gas sensors based on the microwave Fano resonances. In fact, greenhouse gases have refractive indexes values close to that of the air which makes them very difficult to differentiate. Hence, the Fano-resonance, which is known for its high sensitivity, can be exploited to resolve the properties of these gases. Moreover, when the Fano-resonance occurs in the presence of nanomaterials, its sensitivity is much enhanced leading to ultra-sensitive gas sensors. The proposed sensors are targeted to detect and measure the concentration of the H2S, NOx, SOx and CO2 gases, commonly found in the oil wells.  Recommended Student Academic & Research Background:Physics, optics, Electromagnetics, Electrical engineering, computational methods ​ ​

BAS/1/1605-01-01

Physics, Photonics, Electrical Engineering ​​

​Objectives: Learn the basics of plasmonics and light-matter interaction at the nanoscale; understand the mechanism of Fano resonance and its potential use for sensing purposes; Deliverables: model a sensor based on the concept of Fano resonance and test its efficiency in detecting toxic gas.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Hardware Benchmarking of Deep Neural Networks

Academic Program: Electrical Engineering

Artificial Intelligence is gaining popularity recently. Even though most of the efforts have been put from the software aspects, an efficient hardware execution environment is a must to realize them in practice. Two promising generic hardware solutions for efficient DNN realizations are FPGAs and GPUs. When both of them compared, FPGAs seem to provide the best efficiency/energy consumption. On the other hand, they cannot provide the enough accuracy and performance as GPUs can. Therefore, the correct hardware selection depends on the DNN specifications. At that point, benchmark results of these two architectures with respect to DNN types (e.g., detection, classification, localication, etc.) becomes very important.  Recommended Student Academic & Research Background:Basic knowledge of deep learning, programming, GPUs, FPGAs, AI, Programming​ ​​

BAS/1/1605-01-01

Electrical Engineering, Computer Science ​​

Objectives: To provide extensive benchmarking results and comparison between FPGAs and GPUs for different DNN types. Tools to learn: Pytorch, GPUs, NVIDIA Tools, FPGAs​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

A High Level Synthesis Framework for Spiking Neural Networks

Academic Program: Electrical Engineering

Nowadays, AI is defined as the new electricity powered by the deep neural networks (DNN). Even though DNNs resembles the human brain, it is considered as the first generation of the neural networks. On the other hand, there are other types of neural networks closer to the human brain in terms of the behaviour. Spiking Neural Networks (SNNs) can be considered in this class of neural networks and called as second generation neural networks. Even though the neuron of SNNs can resemble the human brain more closely, their hardware realizations become more costly and complicated. Therefore, an effiicient high level synthesis framework could be very helpful for the researchers working in this area.Recommended Student Academic & Research Background: ​Logic circuits, basic HDL coding, programming, VHDL, Verilog, CS​​ ​

BAS/1/1605-01-01

Computer Science, Neuroscience, Electrical Engineering ​​

Objectives: To provide a toolset for high level synthesis of SNNs that synthesizes the corresponding HDL of the provided SNN. Tools to learn: Python, HDL, FPGA, Cadence Tools ​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Brain Inspired Computing

Academic Program: Electrical Engineering

Diagnostics become more important in third world countries as the people have limited access to medical care systems and have less awareness of healthy lifestyles. There is certainly a need for on-site detection in the life science fields; and for point-of-care diagnostics in rural areas of underdeveloped countries so that even an unskilled person can use the device to determine the presence of disease-causing markers. Currently, diagnostics commonly employ long assay time, trained personnel, sophisticated instruments, and require financial support. A good approach to overcome this current situation would be the use of flexible and paper-based point-of-care devices to detect specific biomarkers. Biomarkers provide insight into normal biological processes, pathogenic processes, and pharmacological therapeutic interventions. Hence, the development of more compatible, reliable, convenient, simple, easyto- use systems would be of great use to a person less skilled in medical diagnostic procedures.​​​​​

BAS/1/1605-01-01

​Electrical Engineering, Computer science, physics, neurosciences

​1-      A complete biosensor design and simulation  2-      Potential fully operational Hardware device  3-      Full detailed report on the design and participation in manuscript and papers writeup​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Biomedical Sensors

Academic Program: Electrical Engineering

Conventional computing based on Von Neumann architecture has been shown to be approaching its limits in scalability and power consumption. If solved with contemporary machines, today’s applications in science and industry related to data analysis, pattern recognition and prediction would demand a huge computing power. In the era of ubiquitous sensing and data acquisition, a way to cheaply and power efficiently make sense of the collected ‘big data’ is of utmost importance. Here, human brain’s efficiency becomes the ultimate standard and inspiration for any future technology. Such trend of understanding the brain behavior is currently gaining a huge attention worldwide. At the sensors lab, students under the supervision of Prof. K.N. Salama are exploring new computing technologies miming the way our brains process and store data.​​​​

BAS/1/1605-01-01

​​Electrical Engineering, Computer science, physics, neurosciences

 Report of state of art brain inspired computers;   Implementation of state of art; Exploration of neuromorphic architectures;  Simulation and comparison of various alternatives​. ​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Internship on Statistical Methods for Brain Signals

Academic Program: Applied Mathematics and Computer Science

The student will learn the state-of-the-art methods for pre-processing and modeling brain signals (in particular, electroencephalograms (EEG)). The student will explore various measures of brain functional and effective connectivity through numerical simulations and actual EEG recordings during various learning tasks. At the end of the internship, the student is expected to submit a written report, a poster and give an informal seminar in the Statistics Program. ​​​​

URF/1/1713-01-01

​​Computer Science, Engineering, Statistics, Applied Mathematics, Economics, Physics.

​At the end of the internship, the student is expected to submit a written report, a poster and give an informal seminar in the Statistics Program.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Development of a novel Stimulated Raman Scattering microscopy system

Academic Program: BioScience

Microscopy techniques based on vibrational spectroscopy are poised to be part of the next generation of microscopes for biological applications based on their unique chemical contrast and sub-cellular resolution for non-invasive, non-destructive and label free imaging of biological samples as live cells. The project will focus on the development of a fast and low-noise detection system in a setup for microscopic vibrational spectroscopy based on Stimulated Raman Scattering, which is one of the most advanced and sensitive methods for label-free microscopy for bio-imaging. The system will be applied to vibrational imaging of cancer stem cells to unveil their specific bio-chemical signatures. ​ ​​​​

ASP/1/1669-01-01

​Electrical Engineering, physics

​Learn Coherent Raman Scattering techniques. Design, assemble and test circuitry for multiplexed and low-noise detection in a Stimulated Raman Scattering microscopy setup based on femtosecond broadband laser sources. Demonstrate fast and high S/N ratio imaging with multiplex (broadband) Stimulated Raman Scattering microscopy. ​ 

BioScience

Biological and Environmental Sciences and Engineering

Novel Micro-optical structures on optical fiber tip with two-photon lithography

Academic Program: BioScience

Optical fibers are nowadays an ubiquitous core element of telecommunication systems, new laser technologies and biomedical devices. Manufacturing techniques for optical fibers have been developed and refined in order create manifold geometries and optical properties (e.g.Dual clad fibers, fiber bundles, Photonic Crystal Fibers, to name a few). Yet the capability to fabricate complex miniaturized structures integrated with optical fibers to realize important optical functions (like beam shaping, beam deflection, fiber optical tweezers, etc.) has been demonstrated only very recently.The project will focus on the fabrication of optical wave-guiding structures on the tip of optical fibers exploiting to flexibility, resolution and 3D fabrication capability of Laser Direct Writing based on Two-Photon Lithography (TPL).​ ​​​​

ASP/1/1669-01-01

​Electrical Engineering, physics

​Learn Two-Photon Lithography. Design structures using wave-optics propagation software. Fabricate structures on optical fibers. Measurements to assess optical function of fabricated structures.​

BioScience

Biological and Environmental Sciences and Engineering

Ultraviolet materials and devices

Academic Program: Electrical Engineering

Ultraviolet light (UV light) plays an increasingly important role in water sterilization, chemical detection and communication. This project aims to develop high efficiency, high power and portable UV light emitting devices using semiconductor materials and nanostructures.​​​

BAS/1/1614-01-01

​Engineering, Physics, Mathematics, Science

​Obtain luminescence in UVB and UVC spectrum range with semiconductor materials and structures. Develop electrical injected UVB and UVC LEDs and lasers. 

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Superluminescent diodes

Academic Program: Electrical Engineering

This project aims to study novel characteristics of blue and green InGaN-based laser diodes and superluminescent diodes, including electro-optical characterization, fabrication, and applications as in solid-state lighting (SSL) and visible light communication (VLC).​​

BAS/1/1614-01-01

​Engineering, Physics, Mathematics, Science

​Learning of InGaN-based laser and superlumininescent diode characteristics, physics, and state-of-the-art. Potential conference/journal publications.​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

High speed photodetector

Academic Program: Electrical Engineering

This project aims to find solutions for high speed communications in free space and underwater environment. The receiver of photodetectors in the communication link needs to be tailored for specific light detection with high modulation speed.​

BAS/1/1614-01-01

​Engineering, Physics, Mathematics, Science

​Design of InGaN and AlGaN based photodetector for visible and UV light communication. Bandwidth of the devices needs to achieve MHz to GHz range.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Underwater Optical Communication

Academic Program: Electrical Engineering

More than two-thirds of the Earth’s surface is covered by water. The oceans and seas play a critical role in many of the Earth’s systems including climate, weather and food production cycles. Even though underwater communications have been under research since long time ago, most of the underwater world still remains unexplored so far. To further explore the underwater environments, developing efficient communication technology is of crucial important.Underwater wireless transmission can be achieved through radio, optical, or acoustic waves. Transmission of signal through radio water is limited to a few tens of meters. Although long distance transmission of acoustic waves has been demonstrated, transmission of signal through this technique offer a low data rate of 20 kbps.In this project,our goal is to develop a high data rate line-of-sight and non-line-of-sight underwater wireless optical communication system using highly coherent, either broad or narrow beam divergence semiconductor lasers.  When developed, this giga-bit bandwidth, kilometer range underwater communication system will enable many novel applications includes seafloor survey, underwater oil field exploration, etc. ​​​​​

BAS/1/1614-01-01

​Electrical Engineering, Applied Physics

​Demonstrate the transmission of high bit-rate signals in water channel using laser diodes. ​ 

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Solar Hydrogen Fuel Generation

Academic Program: Electrical Engineering

The expected depletion of fossil fuel reserves and its severe environmental impact have emphasized the need for sustainable and clean energy resources. Solar hydrogen fuel generation by water splitting using sunlight, water, and semiconductors is a promising alternative to conventional fossil fuels, which has great potential to relieve energy and environmental issues and bring an energy revolution in a clean and sustainable manner. To be practical, solar hydrogen production via water splitting needs to tackle the challenges of high solar-to-hydrogen (STH) energy conversion efficiency and high stability of the materials and devices. In photoelectrochemical (PEC) water splitting, as an example, the bandgap of semiconductors, band-edge potentials, optoelectronic efficiency, and stability must be satisfied simultaneously to improve the STH efficiency. In this regard, extensive research efforts have been devoted to address these challenges.In this project,our goal is to fabricate a stable semiconductor photoelectrode that can absorb the visible light as well as produce a high rate of hydrogen fuel. The student engaged to this research activity will be able to receive a high-quality training and gain a valuable experience in the field of semiconductor nanostructures fabrication and the solar hydrogen generation, which can help his future career significantly in the academic and the industrial fields.​ ​​​​​​

BAS/1/1614-01-01

​Electrical Engineering, Applied Physics

​Demonstrate the process of photoelectrochemical water splitting for solar hydrogen fuel generation.​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Underwater wireless optical communications

Academic Program: Electrical Engineering

​Recently, underwater wireless optical communication (UWOC) has been proposed as an alternative or complementary solution to acoustic and radio frequency (RF) underwater communication links over short and moderate distances (<100m) to alleviate the current problem of low data rate and large transmission delays. UWOC uses visible blue-green (400-550 nm) laser diodes to establish secure, efficient and high data rate communication systems. However, the underwater environment is optically very challenging. The propagation of laser beams in seawater is significantly affected by absorption scattering, and turbulence. In KAUST, we are experimentally addressing these challenges. We developed an experimental test-bed in the laboratory with an embedded water tank to simulate the ocean environment. ​​​​

BAS/1/1614-01-01

​Electrical engineering or physics

​Students involved will focus on developing experimental and theoretical models tobetter understand the underwater optical channel and the effects of turbulence, absorption, and scattering in different waters and at different depths. In particular, the focus is on investigating bit error rate (BER) performance under air bubble, temperature and salinity induced oceanic turbulences, and developing a comprehensive and unified statistical turbulence model for the ocean.​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Teaching Cars to Drive and UAVs to Race

Academic Program: Electrical Engineering

At the Image and Video Understanding Lab (IVUL) at KAUST, we have developed a photo-realistic simulator (denoted UE4Sim) based on the open-source computer game engine Unreal Engine. The UE4Sim simulator has been designed to facilitate the integration of computer vision and machine learning techniques into a realistic looking 3D environment with the following advantages. (1) By facilitating the generation of 3D worlds, UE4Sim enables the quick and automatic acquisition of large amounts of labelled data to be used for training data-hungry machine learning models (specifically deep neural networks) targeting a multitude of computer vision and machine learning applications ranging from self-navigating cars/drones and aerial tracking to indoor 2D/3D scene understanding and 3D reconstruction. (2) UE4Sim provides simple-to-use connections with third party software to allow for real-time evaluation of AI techniques. The photo-realism of UE4Sim facilitates the transfer of the learned models to the real-world. In this internship project, we plan to develop UE4Sim further, motivated by the goal of teaching a car to drive in previously unseen scenarios and unmanned aerial vehicles (UAVs) to race through obstacle courses. All this functionality will be done within UE4Sim with an ultimate aim at transfer this learned knowledge to real world vehicles. ​​

BAS/1/1653-01-01

​Electrical Engineering or Computer Science

Improvements on the UE4Sim simulator to make it more streamlined, efficient, and developer friendly for future development and integration with various types of learning (e.g. deep learning and reinforcement learning)Development of deep learning methods to estimate future positions of the vehicles (called waypoints) directly from images (perception network) Development of reinforcement learning methods to generate the appropriate vehicle controls, e.g. steering wheel angle or pitch/yaw/roll (control network) System integration of the perception and control network within UE4Sim​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Persistent Automated Tracking from Unmanned Aerial Vehicles (UAVs)

Academic Program: Electrical Engineering

Empowering unmanned aerial vehicles (UAVs) with automated computer vision capabilities (e.g. tracking, object/activity recognition, etc.) is becoming a very important research direction in the field and is rapidly accelerating with the increasing availability of low-cost, commercially available UAVs. In fact, aerial tracking has enabled many new applications in computer vision (beyond those related to surveillance) including search and rescue, wild-life monitoring, crowd monitoring/management, navigation/localization, obstacle/object avoidance, and videography of extreme sports. Aerial tracking can be applied to a diverse set of objects (e.g. humans, animals, cars, boats, etc.), many of which cannot be physically or persistently tracked from the ground. In particular, real-world aerial tracking scenarios pose new challenges to the tracking problem, exposing areas for further research. Visual tracking on UAVs is a very promising application, since the camera can follow the target based on visual feedback and actively change its orientation and position to optimize for tracking performance. This marks the defining difference compared to static tracking systems, which passively analyze a dynamic scene. In this project, we will develop novel tracking strategies that are designed for real-time operation on a UAV. These tracking methods should be fast, reliable, and accurate. For evaluation purposes, we will use the newly developed aerial tracking benchmark that the IVUL group has developed. Moreover, we will test out these trackers within the aerial simulator that the IVUL group developed based on a photo-realistic game engine and a VR setup, which allows the user to move the object to be tracked in the simulated environment. Finally, these tracking methods will be embedded in a fully functioning UAV, which will be able to automatically and persistently track an object of interest on the ground.​​​​ ​​​

BAS/1/1653-01-01

​Computer, Electrical , Mathematical Sciences , Engineering​

​Statistics on the nuisances commonly faced in aerial tracking scenarios. Novel techniques to track a single object from a single aerial viewpoint. Novel techniques to search for an object when it moves outside the field of view of the camera. A fully functioning prototype UAV that runs the tracking method locally and that interfaces tracking results into the UAV’s navigation system.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Large-Scale Human Activity Recognition in the Wild

Academic Program: Electrical Engineering

With the growth of online media, surveillance and mobile cameras, the amount and size of video databases are increasing at an incredible pace. For example, YouTube reported that over 300 hours of video are uploaded every minute to their servers. Moreover, the commercial availability of inexpensive cameras has led to an overwhelming amount of data, of which video streams from surveillance systems have been quoted to be the largest source ofbig data. However, the significant improvement in camera hardware has not been paralleled with accompanying automated algorithms and software that are crucial to intelligently sift through this ever-growing data heap. This situation has become so dire that much of large-scale video content (either online or in local networks) is rarely processed for meaningful semantic information. With such a development, this data merely serves as dense video sampling of the real-world, which is void of connectivity, correlation, and a deeper understanding of the spatiotemporal phenomena governing this data. Arguably, people are the most important and interesting subjects of these videos. The computer vision community has embraced this observation to validate the crucial role that human activity/action recognition plays in building smarter surveillance systems (e.g. to monitor public safety and public infrastructure usage), as well as, to enable business intelligence, semantically aware video indices (e.g. intelligent video search in large databases), and more natural human-computer interfaces (e.g. teaching robots to perform activities by example or controlling computers with natural body language). However, despite the explosion of video data available, the ability to automatically detect, recognize, and represent human activities is still rather limited. This is primarily due to impeding challenges inherent to the task, namely the large variability in execution styles, complexity of the visual stimuli in terms of camera motion, background clutter, and viewpoint changes, as well as, the level of detail and number of activities that can be recognized. In this project, we will address the important problems of human activity detection/classification, summarization, and representation with a suite of algorithms that are capable of efficiently and accurately learning from a newly compiled large-scale video dataset equipped with descriptive, hierarchical, and multi-modal annotations, calledActivityNet. We will investigate different facets of these problems with the ultimate goal of improving state-of-the-art performance in detecting and classifying human activities in real-world videos at large-scales.​ ​​​

BAS/1/1653-01-01

Computer, Electrical , Mathematical Sciences , Engineering

​Novel techniques to classify snippets of video according to the activities they entail Novel techniques to quickly localize “activity proposals”, i.e. temporal segments in video where the probability of finding interesting activities is high. Combining the knowledge of objects and scenes in classifying an activity, since an activity is a spatiotemporal phenomenon where humans interacts with objects in a particular place Crowd-sourcing framework (e.g. using Amazon Mechanical Turk) to cheaply extend the annotations of ActivityNet to object and place classes, as well as, free-form text description. These annotations will enrich the dataset, forge links with other large-scale datasets, and enable new functionality (e.g. textual translation of a video that enables text queries). 

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Augmented Reality with Google Tablets and Glasses

Academic Program: Electrical Engineering

Wearable devices have attracted a lot of attention from the research community. These devices enable access to a user’s day-to-day life. Many of these devices support multi-modal sensors that can record and/or transfer sensory data including video and audio. Coupling this source of data with network connectivity can enable a wide range of augmented reality (AR) applications, which serve to enrich the user’s life and provide more insight in making decisions. For example, a wearable device supported by intelligent computer vision and machine learning methods can automatically infer and relay information about the place and situation to the user directly. This provides the user with more information to make a particular decision, e.g. whether or not to buy a product in a store based on reviews and competitor pricing found online. Moreover, these augmented capabilities could be very beneficial for people with sensory impairments, e.g. a visually impaired person wearing an AR device can be warned (through audio) of immediate obstacles in his/her way or a hearing impaired person can be notified (through words on a display) of someone calling out to him/her. In this project, we aim to build an AR system based on the Google Glass and a Google Tablet, which will automatically acquire visual and audio data and transfer it to a central processing station for analysis. Information inferred from this data will be transferred back to the Glass, so that it is conveyed to the user in visual or audio form. This is possible because the Glass supports both visual and audio sensors. One possible output of this project is the ability to project on the Glass display automatically-generated results of recognizing (i.e. labeling) and detecting (i.e. localizing) objects in front of the user. ​​​

BAS/1/1653-01-01

Computer, Electrical , Mathematical Sciences , Engineering ​

A software module based on the Google Glass SDK to acquire and transfer still images and videos from the Glass to a central processing station and transfer meta-data in the opposite direction. An API for the central processing station to invoke automatic computer vision and machine learning algorithms on the received images and videos. A software module based on the Google Glass SDK that conveys to the user the meta-data acquired from the central processing station on the Glass display. A large-scale dataset of videos and still images captured by a Google Glass during day-to-day activities. The important objects and activities in these videos will be manually labeled and used for training as well as testing the overall system. This dataset will be made publicly available to the research community for future algorithm evaluation and comparison.​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Experimental validation of new neuro-vascular fractional model

Academic Program: Electrical Engineering

The neurovascular coupling is a key mechanism linking the neural activity to the hemodynamic behavior.  Modeling of this coupling is very important to understand the brain function but it is at the same time very complex due to the complexity of the involved phenomena. Many studies have reported a time delay between the neural activity and the cerebral blood flow, which has been described by adding a delay parameter in some of the existing models. An alternative approach has been recently proposed where a fractional system is used to model the neurovascular coupling. Thanks to its nonlocal property, a fractional derivative is suitable for modeling phenomena with delay.  The model has been validated with extensive simulation study.In this project, the student will validate the neuro-vascular fractional model using real cerebral blood flow and Blood Oxygen Level Dependent (BOLD) measurements. This work will be conducted with our collaborators from Ghent University.  ​​

BAS/1/1627-01-01

​​Electrical engineering/ Applied Mathematics

​Expect to submit a paper on this experimental validation​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Computational Bioscience Research Center

Shape recognition using squared eigen-functions of the Schrödinger operator

Academic Program: Electrical Engineering

A new adaptive signal/image reconstruction, analysis and denoising method has been recently developed in our group where the signal is decomposed into signal dependent functions. These functions are the L2-normalized squared eigenfunctions associated to the discrete spectrum of a Schrödinger operator, the potential of which considered to be the signal/image. These signal dependent functions provide a good approximation of the signal and exhibit interesting localization properties, and they supply new parameters that can be used to extract relevant features of signal variations. They also constitute an efficient analysis tool as the information about the signal is continuously reflected on these localized functions.In this project, the student will study the potential use of this algorithm to shape recognition where the new spectral data provided by the method will be combined with data mining approaches with a potential application to red sea marine creature recognition​​

BAS/1/1627-01-01

​Electrical engineering/ Applied Mathematics/Signal processing/Data mining

​A shape recognition algorithm will be provided with Matlab or C++ implementation.-         A paper will be submitted  ​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Computational Bioscience Research Center

Optimization, control and monitoring of solar driven desalination systems

Academic Program: Electrical Engineering

Membrane distillation (MD) is a thermally driven distillation process. In this process, hot feed stream is passed along one side of a hydrophobic membrane, which is only permeable for water vapor and retains liquid water, whereas the other side is kept at a lower (cooler) temperature. Due to temperature difference across the membrane, water evaporates at the feed-membrane interface and the induced partial vapor pressure difference drives only water vapor through the membrane where it condenses on the other side of the membrane, called the permeate side. MD requires low-grade heat, which can be harvested from solar thermal energy, and other renewable or waste heat sources. Also, unlike the well-known reverse osmosis, MD operates at a lower water pressure, which in turns reduces the capital and operational costs. All these advantages make MD ideal for remote area desalination plants installations with minimal infrastructure and less demanding membrane characteristics.  However, MD is faced with challenges that are yet to be addressed in order for this technology to be competitive with conventional desalination techniques. In recent years, MD has been coupled with renewable energy sources, such as solar thermal collectors and photovoltaic (PV) panels, to capitalize on the attractive features of MD. However, the unsteady nature of renewable energy sources imposes a challenge on solar powered membrane distillation (SPMD) that requires special attention on process modeling and system control. Moreover, over time, membrane permeability changes due to scaling and fouling. All these factors have to be taken into consideration when modeling MD. In this project, the student will design an optimal control strategy to control the productivity of the combined solar-MD system under different constraints.  He will also design monitoring strategies for fouling detection using estimation methods. Experimental validation will be performed in collaboration with Water desalination and Reuse center at  KAUST.​​

BAS/1/1627-01-01

Taous-Meriem Laleg-Kirati

Solar

​Electrical engineering/ Applied Mathematics/Control Theory

​Controller will be deigned and tested by simulations and if time will allow experiments will be performed.-         A paper will be submitted​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Undergraduate

Computational Bioscience Research Center

Wireless Networks for Better Smart Buildings

Academic Program: Computer Science

Smart building involves a construction of multiple layer system that is capable to sense, acquire, analyze and perform the proper action to maintain the operation of certain city entity. The layered system incorporates six layers including: sensing layer, network layer, software layer, semantic discovery layer, processing and reasoning layer, and service layer. All the statistics show that there will be a large demand for smart buildings in the future as it has the potential for energy saving, indoor services such as tracking, mapping, localization, identifying products, and downloading relevant information are the main drive for future trends. The number of smart devices is expected to be x10 of the current number in 2020. Efficient Resource allocation for context aware based systems with the future demand for smart devices is challenging. Thus, it is essential to utilize techniques such as data mining and machine learning for data analytics, reasoning, and decision-making in order to maximize the smart building operation efficiency and overcome all the related challenges.​​

BAS/1/1601-01-01

​Computer Science

​The student will consider smart building services as a core for gathering data. Such data can be collected and transmitted in several ways. However, we will be interested in wireless technologies as a platform using simple devices such as smart phones. We gather the data and use data mining and machine learning techniques to make the right decisions such that we guarantee the sustainability of the smart building services.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Realtime transmission in Underwater Wireless Environments

Academic Program: Computer Science

Design and implement a system that facilitates realtime data transmission in underwater wireless networks. This includes examining the data transmission over several types of water conditions along with extracting the data transmission characteristics.  ​​

BAS/1/1601-01-01

​Computer science and/or electrical engineering

​The student is expected to closely work on an underwater wireless optical transmission testbed. Using the testbed equipment’s, the student will be running several sets of experiments and collect certain data (e.g., bit error rates, frame rates, channel condition, ..etc). The extracted data will be later used to design an optimal resource allocation framework for facilitating realtime transmission in such environments. ​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Wireless Sensor Node Analysis Employing Energy Harvesting

Academic Program: Computer Science

The project consist of a theoretical and a system research thrusts in energy-harvesting wireless sensor networks. Looking at the energy harvesting module in sensor node from the system’s prospective, we observe that adopting an interruption/harvesting policy enhances the energy consumption, but it also increases average packet end-to-end delay and packet dropping! There are various tradeoffs exist in wireless sensor network (WSN) design. Of particular interest to the project are 1) End-to-end delay vs. energy harvesting & network size, and 2) Increasing network size allows for a smaller number of data sink nodes and reduces dropping but it also increases average end-to-end delay. In order to quantify the tradeoffs, we raise a question. How delay, network size, and harvesting policy (service vacation) interact with each other? In other words, how large the network dimensions can go to considering certain packet latency threshold and dropping? Energy harvesting module can arbitrary be triggered, upon empty buffers, and thus, imposes random interruption periods on the sensor node, these random cycles (vacations) increases latency due to residual vacation time that is consumed for harvesting. In order to solve the above challenge, the student will study this system and think of a theoretical and a system approaches (with the assistance of the instructor) to improve the end-to-end delay. For instance, a possible solution would be, instead of arbitrary harvesting time, we aim at optimizing this value to minimize the delay and dropping. We also aim at adding a constraint that forces the sensor node to trigger the harvesting phase once its battery is low! Currently, the networking lab has a set of 20 sensor motes that are programmable using TinyOS and also has all the necessary mathematical packages to evaluate the student proposed models. ​​​

BAS/1/1601-01-01

​Computer science and electrical engineering

​The student is expected to achieve:1.      (theatrical component): An optimization of the energy harvesting value that minimizes the system end-to-end delay validated using matlab. 2.      (systems component): Translate the results from (1) into a working code, which can be tested over our TelosB sensor motes using TinyOS (C/C++).   The above results, if completed, are considered novel and can result into a publication with the agreement with the instructor.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

High Pressure Heterogeneous Autoignition of Hydrocarbon and Syngas Fuels

Academic Program: Mechanical Engineering

Work with postdoc on new high pressure vessel to measure the autoignition characteristics of gaseous fuels​​

BAS/1/1370-01-01

​Mechanical Engineering, Chemical Engineering, Aerospace Engineering, Physics.​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

CESE solver on GPUs for real gas flow simulations

Academic Program: Applied Mathematics and Computer Science

The project focuses on the extension to more complex thermodynamic models and equation of states of a two and three dimensional compressible fluid dynamic solver for the Euler and Navier–Stokes equations. Specific interest are developed to the implementation and use of the polytropic van der Waals (PvdW), and the polytropic Peng-Robinson (PR) models in one of the compressible solver available in our research group. The goal is to investigate and asses the accuracy of the PvdW and PR models coupled with the the so-called conservation element and solution element (CESE) algorithm for simulating nonideal compressible fluid flows. The latter is a branch of fluid mechanics which studies the characteristic of dense va- pors, supercrtical flows, and compressible two-phase flows where the thermodynamics of the fluid differ substantially from that of the perfect gas. In fact, in particular thermo- dynamic conditions, the fluid flows may exhibit nonclassical gas-dynamic phenomena, e.g., expansion shock waves. The application of nonideal compressible fluid flows in industry is already widespread. They can be found in CO2power cycles, pharmaceu- tical processing, transport of fuels at high-speed, organic Rankine cycles for power conversion. Therefore, an accurate understanding of the complex physics behind fluid flows that differ substantially from that of the perfect gas would undoubtedly pave the way for introducing technological improvements in real-world applications. A number of research projects are actively ongoing for better understanding and modeling non- ideal compressible fluid flows and defining implications in terms of engineering design. However, as already shown several researchers, the accuracy of the thermodynamic model has a strong influence on the simulation of nonclassical phenomena, to the point that their presence can depend on the accuracy with which fluid model parameters are determined. Thus, a high-fidelity and highly accurate simulation of nonideal compress- ible fluid flows is of paramount importance and can provide considerable insights both for the study of nonideal thermodynamics and engineering design and optimization.  In this projects, the CESE algorithm coupled with a the PvdV and PR thermodynamic model will be used. The subsonic inviscid flow over a NACA-0012 airfoil, the tran- sonic inviscid flow over a NACA-0012 airfoil and the Prandtl-Meyer expansion will be used for the assessment of the numerical accuracy and efficiency of the new solver for nonideal compressible fluid flows.  ​​​​​

BAS/1/1663-01-01

​Applied Mathematics and Computational Science; GPU programming; Compressible Flows

 Implement new thermodynamic models in an existing, high preformat CESE code, port fundamental part of the solver to single and multiple GPU and solve some canonical but extremely important test problems to validate the solver​ 

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Extreme Computing Research Center

3D/Inkjet Printed Cube Satellite Transparent Antenna Design

Academic Program: Electrical Engineering

A CubeSat (Short form of Cube Satellite) is a miniaturized satellite (of the order of 10 cm3) intended for a number of space research applications in the Low Earth Orbit (LEO). CubeSat are typically launched by deployers from the International Space Center. The concept of CubeSat was introduced to lower the cost associated with launches as it can be launched as a secondary payload on the launch vehicle.This project will focus on an innovative antenna design for CubeSat which is expected to cover the entire frequency band for the application and also provides near isotropic radiation pattern with decent gain performance. In order to lower the cost as well as weight, additive manufacturing techniques such as 3D and Inkjet printing will be employed. An important aspect is to make this antenna transparent as it should not block the light coming to the on board solar cells. So a transparent material will be explored which can be compatible with the printing processes. It will also be considered that the antenna design occupies minimum space on the CubeSat surface. This project will enable student to first design an innovative antenna in industry standard electromagnetic simulators, realize it through printing techniques with the state of the art printers in KAUST and then test it in latest anechoic chambers available in IMPACT Lab KAUST.​​​​​​

BAS/1/1622-01-01

​Electrical Engineering

​Optimized Design of Cube Sat Antenna through EM simulations3D Inkjet Printed Prototype Test results of fabricated prototype Short report of the project​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Advanced Terahertz Source Generation using Plasmonic Photomixers

Academic Program: Electrical Engineering

Photomixers are one of the most promising sources of continuous-wave terahertz (THz) radiation with excellent frequency tunability and high spectral purity while operating at room temperature. The objective of this project is to develop a new generation of high-performance photomixers that enable new functionalities for practical THz imaging, sensing, and communication systems that are not possible through existing technologies. Specifically, we plan to utilize plasmonic nanostructures inside photomixer active area to enhance its optical-to-THz conversion efficiency and THz radiation power by several orders of magnitude. This project will enable student to understand and design nano-plasmonic structures in industry standard electromagnetic simulators. The student will also be able to participate in the nano-fabrication process of these structures (under the supervision of an expert postdoc) in KAUST nano-fabrication facilities.​​​​

BAS/1/1622-01-01

​Electrical Engineering

​Optimized Design of photomixersPrototype fabrication in clean room facilitiesShort report of the project​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Inkjet Printed Wireless Temperature and Humidity Sensors for Smart Bandage Application

Academic Program: Electrical Engineering

In this project, the student will first learn inkjet printing in the lab. Then the student will design temperature and humidity sensors. These will be electrical sensors, specifically resistive and capacitive sensors. These sensors will be printed on a wearable bandage to determine the temperature and humidity levels in the wound. The bandage will also have a wireless part which will send this data to the cell phone in a wireless fashion. The project involves design, fabrication and characterization so the student will go through the entire cycle of a research project.​​​​

BAS/1/1622-01-01

​Electrical Engineering

​test

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Inkjet Printed Flexible RF Energy Harvesting Module

Academic Program: Electrical Engineering

In this project, the student will design a flexible antenna in an EM simulator to collect RF energy. Then the student will learn inkjet printing in the lab. The designed antenna will be printed on a PET or a PEN substrate. The antenna will be integrated with a custom rectifier chip (previously done). The student will need to do the layout for mounting of the chip on the antenna substrate and will also integrate the chip with the antenna. Finally, characterization of the complete energy harvesting module will be done through an RF source and suitable load.​​​​

BAS/1/1622-01-01

​Electrical Engineering​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Dynamics of MEMS for mechanical computing

Academic Program: Mechanical Engineering

The dynamic behavior of micro-electromechanical systems MEMS devices will be simulated to achieve logic functions such as OR, AND gates. The project will require building a model for MEMS resonator and running computer simulations to help in the design of these resonators; so that they are eventually fabricated and tested. The project requires basic programming skills, which are commonly mastered at the undergrad level of engineering. ​​​

BAS/1/1379-01-41

​Mechanical engineering​

Mechanical Engineering

Physical Sciences and Engineering

Design of hydraulic structures to reduce structural damages via multiphase simulations

Academic Program: Applied Mathematics and Computer Science

Structural damage caused by large waves such as tsunamis is an important concern in many areas of the world. One approach to mitigate this damage is to alter the phycial environment near the shore; the simplest approach is to place levees or other structures to block oncoming waves.Alternatively, one might try to force the wave to to break away from the shore, in order to dissipate its energy before arriving to the point of interest.In this project, we will consider situations of interest such as wave Propagation in channels and use multiphase flow codes to simulate these scenarios.Our goal is to explore alternatives for the design of hydraulic structures to protect specific points of interest. ​​​​​

ASP/1/1669-01-01

​Applied mathematics and computational science

​Numerical simulation of proposed wave mitigation techniques​ 

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Iterative algorithms for scalar conservation laws and volume of fluids

Academic Program: Applied Mathematics and Computer Science

Development of algorithms for convection-dominated problemsundercompressible flows is an important topic for applications like sediment transport.If the transport of a quantity saturates then the solution of the transport equations must be bounded by physical constraints. This process could in principle be modeled via the constitutive relations of the flow model. Alternatively, one could impose algebraicconstraints in the transport solver to guarantee the physical bounds.With this project we aim to review recent methods for solving transport equations (under compressible flows) that impose physically motivated bounds on the solution.In addition, we are interested on exploring novel methodologies based on flux correctionfor continuous Galerkin finite elements to achieve the desired goals.​​

BAS/1/1616-01-01

​Applied mathematics and computational science

​Implementation and testing of the proposed algorithm​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Improving conservative level-set methods for multiphase simulations

Academic Program: Applied Mathematics and Computer Science

This projects starts with a newly developed conservative level-setmethodfor multiphase flows. This method combines ideas from the level-set and the volume of fluid schemes into a monolithic model. The model contains a consistent term that regularizes the Jacobian of the non-linear equation and that penalizes deviations from the signed distance function.The result is a conservative level-set model that does notrequirereconstruction of the interface and that produces an approximation of the signeddistancefunction (to the fluids interface). In the current project we aim to improve the method in the following three fronts: - The current form of the method does not require extra stabilization of the advective term since it depends upon the penalization term. This however, implies that one can't reduce the influence of the penalization or instabilities might start to appear. We want to introduce extra and independent stabilization to the advective term. The model is a conservation law for a regularized Heaviside function. The reason for this is that integration of discontinuous functionsrequiresnon-standard methodologies within the context of finite elements.We plan to use state of the art integration techniques that would allow us to use exact Heaviside functions improving the conservation properties and overall quality of the solution. - The model contains a user defined parameter. To obtainqualitativelygood results one might need to select this parameter depending on the problem. This dependency can be mitigated via optimal control theory that would allow the algorithm to automatically select an optimal parameter for any given problem. We plan to test each modification to the method via a set of well established benchmarks in the area of multiphase flows.​​

BAS/1/1616-01-01

​Applied mathematics and computational science

​Implementation and testing of the proposed algorithm​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Modeling shallow water waves via CG-FEM with monolithic convex limiting

Academic Program: Applied Mathematics and Computer Science

​Structural damages due to big and strong waves is an important problem for different locations.One can place levees or other structures to reduce the impact of such waves on specific locations of interest. However, other approaches might be useful.For example, one can try to reflect most of the energy of a wave before it reaches a point of interest. Alternatively, one can force the wave to dissipate its energy before arriving to the point of interest.In this project we will consider a few problems of interest such as wave propagation in channels and use multiphase flow codes to simulate these scenarios. Our goal is to explore alternatives for the design of hydraulic structures to protect specific points of interest.​ ​​​

ASP/1/1669-01-01

​Applied mathematics and computational science

​- Implementation of monolithic convex limiting in an existing finite element code- Comparison of this technique with existing algorithms​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Exact versus approximate Riemann solvers for finite volume methods

Academic Program: Applied Mathematics and Computer Science

Riemann solvers are the core computation in some numerical methods for hyperbolic conservation laws. For such methods, the Riemann solvers are one of the most computationally demanding part of the entire algorithm. For this reason a common strategy is to develop efficient methods that approximate the solution of a Riemann problem.In recent years some highly efficient iterative algorithms have been proposed to approximate the solution of Riemann problems to arbitrary precision.This suggests that one could obtain the exact solution of Riemann problems (up to machine precision) in few iterations.As a result, one could attempt to consider the exact solution of Riemann problems instead of the more standard approximations without an excessive over head on computational cost.In this project we are interested on using state of the art exact Riemann solvers within the context of high-order finite volume methods and compare the overall quality, computational cost and robustness of the solution versus more standard approximate Riemann solvers. To do this we plan to concentrate on the Euler equations and the shallowwater model. ​​​

BAS/1/1616-01-01

​Applied mathematics and computational science​

​- Implementation of exact Riemann solvers for Euler and Shallow water equations, with high-accuracy initial guesses- Comparison of performance between exact and approximate Riemann solvers on a range of test problems, using PyClaw​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

A domain- specific language and code generation for Riemann solvers

Academic Program: Applied Mathematics and Computer Science

Riemann solvers are the core algorithms in numerical methods for wave propagation. They are also the most complex part of developing code for new applications. The design and implementation of an effective approximate Riemann solver typically requires substantial expertise and time. However, there exist generic approaches that utilize relatively straightforward properties of the hyperbolic system and are reasonably efficient. The goal of this project is to develop a domain- specific language for hyperbolic conservation laws and Riemann solvers, and implement automatic generation of efficient solvers based on a purely symbolic representation of the problem.  ​​​​​

BAS/1/1616-01-01

​Mathematics, computer science or engineering

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Laser-based Sensor Design and Development

Academic Program: Mechanical Engineering

The project involves design, development, and implementation of a laser-based optical sensor. The sensor will be used to monitor environmental pollutants (e.g., NOx, CO) or greenhouse gas emissions (e.g., N2O, CH4, CO2). The student will work on studying the electromagnetic spectrum of various molecules, choosing the candidate optical transitions, setting up the laser-based optical setup, and performinglaboratory measurements to detect species concentration in trace quantities. Advanced sensing strategies, such as wavelength modulation, cavity-enhancement and frequency combs will be utilized. The student will gain expertise in spectroscopy,statistical thermodynamics, machine learning, optical engineering, and mechanical design.​​​

BAS/1/1300-01-01

​Physics, Electrical Engineering, Mechanical Engineering, Chemical Engineering

​Spectral line selection using state-of-the-art spectroscopicmodels Design of optical, electronic and mechanical components of thesensor Laboratory validations of the sensorperformance ​Field testing for trace gasdetection​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Future Fuel for Advanced Combustion Engines

Academic Program: Chemical Science

Increasing focus on global warming and CO2 emsisions is pushing the engine technology to new frontiers. The overarching objective is to increase the efficiency of internal combustion engines so as to minimize the CO2 emissions. Advanced engine technologies revolve around compression ignition concepts but diesel is not deemed to be suitable fuel for achieving higher efficiency and low pollutant levels. In this context, we are exploring new fuel formulations which can be produced at a lower cost from the refinery but can provide superior performance in the engine. The project will involve exploring the ignition and emission characteristics of such candidate future fuels.​​​​​

BAS/1/1300-01-01

​Mechanical Engineering, Chemical Engineering, Chemistry

​Perofrm detailed physical/chemical characterization on select refinery stream fuels;Carry out ignition experiments in idealized reactor configurations of shock tube and rapid compression machine; Perform chemical kinetic modelling to develop surrogates for the fuels; Analyze the performance of new fuel in engine simulations; Recommend the optimal fuel formulation suitable for advanced compression ignition engines​.

Chemical Science

Physical Sciences and Engineering

Clean Combustion Research Center

Chemical Kinetics of Novel Biofuels

Academic Program: Mechanical Engineering

Biofuels are becoming increasingly important in the world's energy infrastructure and their use has steadily been increasing in Europe and the U.S. With a number of candidate biofuels, a concentrated effort must be spent on choosing the optimal fuel that can be produced in a cost-effective manner and deliver the best performance within the engine. The student will initially work on choosing a few candidate biofuel molecules for investigating experimentally in the laboratory. Thereafter, he/she will perform a series of experimental studies on the selected fuels to understand their chemical kinetics behavior.​​​​​​​​​

BAS/1/1300-01-01

Mechanical Engineering or Chemical Engineering

- Perform life-cycle-analysis to select candidate biofuels - Characterize various biofuel molecules in terms of their physical properties - Conduct detailed experiments on the chemical kinetics behavior of these biofuels using shock tube and rapid compression machine - Run validated chemical kinetics models to estimate the performance of studied biofuels in an engine - Show how the new fuel leads to improvement in engine efficiency and reduction in emissions ​​​​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Theoretical and numerical study on complex materials

Academic Program: Applied Mathematics and Computer Science

​The students are required to perform theoretical and numerical studies on wave propagation in artificial structures with complex structures. The contents include but are not limited to Fano resonance, absorption, trapping of electromagnetic or acoustic waves. ​​​​​

BAS/1/1626-01-01

​Physics, Mathematics, Material Sciences, and related

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Nonlinear Partial Differential Models

Academic Program: Applied Mathematics and Computer Science

In this project we will study some nonlinear partial differential equations models that arise in applications ranging from population dynamics, mean-field games, quantum chemistry and mechanics, medicine, quasi-geostrophic flows, and water waves.​​​​​

11111.0000000000

Mathematics or related field

The objective of the project is to study in detail modeling, analytical and numerical aspects of partial differential equations from concrete applications. A final report and presentation will be required. The work will be developed and the guidance of Prof. Diogo Gomes and the Research Scientist Dr. Saber Trabelsi.​

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Classification of long non-coding RNAs

Academic Program: Computer Science

​Long non-coding RNAs (lncRNAs) have been found to perform various functions in a wide variety of important biological processes. To make easier interpretation of lncRNA functions and conduct deep mining on these transcribed sequences, it is important to classify lncRNAs into different groups. lncRNA classification attracts much attention recently. The main technical difficulties are 1) the limited number of known lncRNAs (small training sample size), and 2) the very different lengths of lncRNAs. This project is to apply and further improve the string kernel algorithms developed in Prof. Gao’s group to the lncRNA classification problem. ​​​​​​​

BAS/1/1624-01-01

​Computer science, bioinformatics, electrical engineering, applied mathematics​

The visiting student for this project is expected to finish the following deliverables:1.      Give a throughout literature review on lncRNA classification methods and potential machine learning methods that can be applied to this problem. 2.      Get familiar with the string kernel algorithms developed in Prof. Gao’s group. 3.      Gather an lncRNA dataset to be used as the benchmark set for this research. 4.      Conduct a comprehensive comparative study of the state-of-the-art methods on the benchmark set. 5.      Apply the string kernel algorithms on lncRNA classification and evaluate the performance. 6.      If necessary, improve the string kernel algorithms to achieve better performance.Write a report to summarize the results.

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Computational Bioscience Research Center

Novel Pincer complexes for catalysis

Academic Program: Chemical Science

The student will work on the design and synthesis of 2-amino-pyridine based pincer ligands (3-10 steps) and the preparation of their corresponding transition metal complexes. Students will trained on standard organic synthesis knowledge and Schlenk skills.  For more information see:https://pubs.acs.org/doi/10.1021/acscatal.8b04495​

BAS/1/1334-01-01

​Catalysis and Organometallics​

​Preparation and characterization of new complexes. Development of catalytic applications​ 

Chemical Science

Physical Sciences and Engineering

KAUST Catalysis Center

Role of non-classical hydrogen bonding in organocatalysis

Academic Program: Chemical Science

The student will utilize kinetic (NMR, IR, etc) and computational tools (DFT calculations) to elucidate the role of hydrogen bonding network and in particular the non-classical hydrogen bonding in the thiourea and guanidine-based organocatalysis.  ​​​​​

BAS/1/1334-01-01

​Chemistry

​Assist in the kinetic study and DFT calculations.​ 

Chemical Science

Physical Sciences and Engineering

KAUST Catalysis Center

Frebonics- Nature inspired engineering

Academic Program: Electrical Engineering

Nature has amazing mysteries. The vast ecosystem is balanced in impeccable efficient manner. Take an example, butterfly. How do they choose flowers to fly around? How their wings are so colorful? How to they morph from a larva to a full blown butterfly? How do they fly? All these are essentially vast set of engineering: motor mechanics, materials and bits of devices here and there synchronized via physics and mathematics. In this project, we explore such engineering in nature and inspired by that learning we simply complex engineering to address global challenges and augment the quality of our life. We believe by integration of freeform electronics (physically flexible, stretchable and reconfigurable in shape and size) with robotics we can imagine and create various frebonics which can essentially be used for advanced healthcare like prosthetics, artificial organs, advanced environmental monitoring, security and self-driven vehicular technology. We are presently working on understanding how flowers bloom: from a tiny entity when it blossoms completely – imagine a display system like your 5.5” iPhone when stretched becomes a 55” television. Fusion of electrical engineering, mechanical engineering, bioengineering, chemistry, civil (structural) engineering, computer science, material science and engineering, we envision to make such a singular gadget which can be reconfigured adaptively in shape and size. This is just one example and there are many – we look forward to working with you!​​

BAS/1/1619-01-01

​Electrical Engineering, Mechanical Engineering, Bio Engineering, Computer Science (Robotics, Automation), Civil Engineering (Structural Engineering), Physics, Material Science and Engineering

​Literature survey, programing, fabrication, material and device analysis, device characterization, system integration, oral and written reports.​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

DIY Electronics

Academic Program: Electrical Engineering

We all use electronics. But why electronics design is not pervasive? If we look around, you will see that there are so many innovations taking place with software technology: social media, ecommerce, Apps, etc. The fundamental tenant of software and computer engineering is to empower all. One learns a language (acquires a skill) and has an idea – just makes that happen. We all have tangible problems in our daily life as an individual and as a community. Electronics can empower us, help us to solve those challenges. Therefore, we have to make electronics simple: easy to understand and to learn and more importantly easy to implement. Because such electronics can then be used (same as programing language) by commoners to democratize electronics. In that regard, recently we demonstrated recyclable materials based paper skin which can function like a natural skin. We see tremendous potential with such materials and we are calling them DO IT YOURSELF (DIY) Electronics. Using various recyclable materials and simplifying complex electronics, we envision to make plug and play DIY Electronics which can be used by all and in that way, we will have citizen science. This is the project for true innovators – those who imagine and make.​​

BAS/1/1619-01-01

​Electrical Engineering, Mechanical Engineering, Bio Engineering, Computer Science (Robotics, Automation), Civil Engineering (Structural Engineering), Physics, Material Science and Engineering

​Literature survey, programing, fabrication, material and device analysis, device characterization, system integration, oral and written reports.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Power Shell Integrated energy network with flexible and stretchable solar cells, hydrogen generators and storage.

Academic Program: Electrical Engineering

We are exploring and developing a large-are curvilinear surface deployable energy network on flexible and stretchable platform which can be used for smart world application specially for civil infrastructure and/or transportation including aero plane to automobile to sea vessels.  The nature of this project is extremely multi-disciplinary: •            Material science and chemistry will let us choose the correct materials. •            Electrical engineering will let us design, fabricate, characterize the energy harvesting and storage devices and their reliability.•            Chemical engineering will allow us to develop chemical processes for fabrication and process integration. ​​​​​​

BAS/1/1619-01-01

​Any relevant field of science or engineering.

​1.. Weekly meetings with the Faculty Advisor. 2.  Weekly written report to the Faculty Advisor. 3.  Monthly presentation.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

More Than Natural Skin

Academic Program: Electrical Engineering

Natural skin is an engineering wonder due to its multisensory capability in a singular platform with simultaneous sensing capability. At the same time, many people have been suffering from skin burns and damages due to acid, burn, wound, etc. Therefore it is an important scientific and engineering challenge to develop an affordable and biocompatible artificial multi-sensory mesoporous singular platform like natural skin and then to integrate that with our neurological system. Paper by virtue of its critical role in our daily life, its physical flexibility, ultra-light weight and affordability make it an amazingly simple but effective material for such skin platform. In the recent past, we have demonstrated a paper based multisensory singular platform which can perform simultaneous sensing. The developed paper skin shows unprecedented functionality and performance over cost. We have tested its effectiveness as environmental sensor as well as for body vital monitor. Therefore, in this project, we will develop and engineer skin like multi-sensory platform for artificial organs and various wearable applications. ​​​​

BAS/1/1619-01-01

Electrical Engineering, Mechanical Engineering, Bio Engineering, Computer Science (Robotics, Automation), Civil Engineering (Structural Engineering), Physics, Material Science and Engineering.

​Literature survey, programing, fabrication, material and device analysis, device characterization, system integration, oral and written reports.​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

First-principles investigation of superlattices of 2D materials

Academic Program: Materials Science & Engineering

The aim of the project is to develop basic insight into the properties of superlattices consisting of 2D materials by first-principles calculations (density functional theory; Boltzmann transport; non-equilibrium Green’s function approach). In general, superlattices are of interest in the field of thermoelectrics, because they give access to designing the phonon scattering and therefore to influencing the thermal transport.Stacking of 2D materials in addition modifies the electronic states at the Fermi level and thus has the potential to enhance the figure of merit. The question of  ion absorption in superlattices is of key importance for battery applications. Because of their high surface-to-volume ratio, 2D materials are intensively studied for various kinds of sensors, while superlattices so far have been considered only rarely in this context. ​​​​

BAS/1/1364-01-01

​Computational Materials Science​

Materials Science & Engineering

Physical Sciences and Engineering

Novel Phenomena at perovskite interfaces and superlattices

Academic Program: Materials Science & Engineering

Superlattices of perovskite oxides often have properties distinguished from their bulk phases. Investigation of these properties is at the​ forefront of modern condensed matter physics and materials science. In particular, after the observation of a highly mobile two-dimensional electron gas at the interface between LaAlO3 and SrTiO3, engineered interfaces are emerging as new horizon for various applications. Using the density functional theory, the project aims at determining the magnetic, electronic, and optical properties of possible perovskite interfaces and superlattices. ​​​​​​​

BAS/1/1364-01-01

​Physics, Materials Science, Chemistry, Electrical Engineering

​​Report. Seminar presentation

Materials Science & Engineering

Physical Sciences and Engineering

First principles modeling of hybrid organic-inorganic perovskites

Academic Program: Materials Science & Engineering

Hybrid organic-inorganic perovskite solar cells have recently emerged as the next-generation photovoltaic technology. Most of the work has been focused on the prototype MAPbI3 perovskite (MA= Methylammonium = CH3NH3+) and its analogues that have lead to power conversion efficiencies in excess of 15%. Despite the huge success, these materials are still non-optimal in terms of optical absorption as the bandgaps are ~1.6 eV and greater. Thus, investigation and development of perovskites with bandgaps closer to optimal, allowing enhanced spectral absorption, is of great interest. The aim of this project is to perform first-principles calculations to study the structural, optical, and electronic properties of new derivatives of MAPbI3 in which the organic MA cation is replaced by other organic amines of similar size and/or the Pb cation is replaced by similar elements. ​​​​​​

BAS/1/1364-01-01

​Physics, Materials Science, Chemistry, Electrical Engineering​

Materials Science & Engineering

Physical Sciences and Engineering

Deep Learning for Visual Computing

Academic Program: Computer Science

The internship will be in the area of visual computing (computer graphics, computer vision, remote sensing). The exact topic depends on the student's interest, student's background, and current research topics in thegroup. To give some examplesof past projects, our group worked on topics related to generative adversarial networks for synthesizing images, textures, point clouds, 3D geometry, ..., networks using graphs as representations, and 3D reconstruction problems such as depth from one or multiple images, primitive fitting, indoor room layout reconstruction and segmentation of images.​

BAS/1/1630-01-01

​Computer Graphics, Computer Vision, Deep Learning

​There are two learning objectives for the internships:1) students should learn about machine learning, deep learning, andtherespective target application chosen for the internship.​2) students should implement a working prototype

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Computer Graphics, Computer Vision, and Visualization

Academic Program: Computer Science

The internship is in the area of graphics, vision, or visualization. The exact topic is determined in discussion with the student to obtain a good fit with the student’s interest and background. Example projects are 3d reconstruction from images and laser scans, geo-spatial visualization, remeshing, sampling, procedural modeling, and design computation using machine learning. ​​​​​​

11111.0000000000

​Computer Science

​The student should either contribute to an existing research project or leading his/her own project. That includes reading literature, solving technical problems, and implementation.​

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Visual Computing Center

Combining deep learning and ontologies

Academic Program: Computer Science

​The project aims to identify applications of deep learning to classification problems involving ontologies, and apply these methods to biological and biomedical datasets. The main challenges of the project are (1) to develop methods that can effectively be applied both to unstructured and structured data and classify instances into classes from ontologies, and (2) to utilize data already structured with ontologies effectively in classification and regression problems. The students will be provided with real-world several datasets and are expected to implement and evaluate deep learning approaches on these datasets. To evaluate the methods on a large scale, students will have access to one of the compute clusters at KAUST.​​​​​​

BAS/1/1659-01-03

​Computer science, artificial intelligence, machine learning, data mining,bioinformatics, or related

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Computational Bioscience Research Center

High-Speed Wireless Communication for Data Centers and High Performance Computing

Academic Program: Electrical Engineering

Design and implementation of optical wireless connections for data center networks. ​​​

BAS/1/1601-01-01;BAS/1/1612-01-01

​Electrical Engineering

​The student is expected to closely work on a novel framework for replacing traditional wired network of data center networks to free space optics. Under the novel framework, the student solves complex optimization problem that involve scheduling mice and elephant flows per servers. ​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Study of Optical Wireless Communication Systems

Academic Program: Electrical Engineering

Network topology. This project can start anytime and is  3 to 12 months in duration. This project is open to Juniors, Seniors, and MS students in Electrical Engineering, Applied Math, and Statistics ​​​​​

URF/1/1713-01-01

Communication, probability, Matlab programing.​

​It is expected that the student will submit one publication to a good venue by the end of his/her internship​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Study of Physical Layer Security Systems

Academic Program: Electrical Engineering

Study of Physical Layer Security System. This project  can start anytime and is 3 to 12 months in duration. This project is open to Juniors, Seniors, and MS students in Electrical Engineering, Applied Math, and Statistics​​​

URF/1/1713-01-01

​​Computer, Electrical, & Mathematical Science​

​It is expected that the student will submit one publication to a good venue by the end of his/her internship

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Study of Massive MIMO Systems for 5 G Networks

Academic Program: Electrical Engineering

​Optimization, Signal processing, Linear Algebra, and Probability.​​​ This projectcan start anytime and is 3 to 12 months in duration. This project is open to Juniors, Seniors, and MS students in Electrical Engineering, Applied Math, and Statistics. ​​​

URF/1/1713-01-01

Computer, Electrical, & Mathematical Science

​It is expected that the student will submit one publication to a good venue by the end of his/her internship​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Energy Harvesting-Based Wireless Sensor Networks

Academic Program: Electrical Engineering

Development of energy efficient large scale wireless sensor networks. This project can start anytime and is 3 to 12 months in duration.  This project is open to Juniors, Seniors, and MS students in Electrical Engineering, Applied Math, and Statistics​​​​

11111.0000000000

​​  Electrical and Computer Engineering (with emphasis on Communications Engineering)

​It is expected that the student will submit one publication to a good venue by the end of his/her internship​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Study of Cognitive Radio (Spectrum Sharing) Systems

Academic Program: Electrical Engineering

Study of Cognitive Radio ( Spectrum Sharing) Systems​​​

URF/1/1713-01-01

​​Computer, Electrical & Mathematical Science

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Development and optimization of algorithms for cloud-enabled heterogeneous radio-access networks

Academic Program: Electrical Engineering

Development and optimization of algorithms for cloud-enabled heterogeneous radio-access networks. This project can start anytime and is 3 to 12 months in duration. This project is open to Juniors, Seniors, and MS students in Electrical Engineering, Applied Math, and Statistics  ​​​​

URF/1/1713-01-01

​​Computer, Electrical, & Mathematical Science

​It is expected that the student will submit one publication to a good venue by the end of his/her internship​

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Adhesion phenomena across interfaces with spatially heterogeneous adhesive properties

Academic Program: Mechanical Engineering

The project aims to explore the effect of heterogeneities on the mechanical behavior of bonded interfaces through integrated experiments and simulations. The research seeks to systematically design multiple sites of potential crack pinning across the interface, able to trigger sequential events of initiation, propagation and crack arrest, thus promoting macroscopic variations of strength and toughness. Inspiration in the search for such novel material configurations is derived from those observed in nature. Successful design of these bio-inspired interfaces can lead to quite interesting technological applications.​​​​​​

BAS/1/1315-01-01

​Mechanical engineering. Material science, civil engineering​

Mechanical Engineering

Physical Sciences and Engineering

Ultra Sensitive Sensors based on Nanotubes Porous Networks

Academic Program: Mechanical Engineering

This project will focus on design, development and implementation of a family of ultra sensitive sensors taking advantage of tunnelling effects in carbon nanotube porous networks. The intertube junctions will be customized by using different materials depending of the sensing needs (moisture, special gas, deformations..) The student will be in charge of defining a simple phenomenological model for each sensing mechanism, of choosing the best material and microstructure configuration for each sensing need and to manufacture, test and validate the resulting prototype. This study is relevant for applications in structural health monitoring and for continuous tracking of biological systems. The student is expected to participate in writing journal publications and presenting research at conferences. ​​​​

BAS/1/1315-01-01

​Mechanical Engineering

​​​

Mechanical Engineering

Physical Sciences and Engineering

Experiments on High-Speed Multi-Phase Flow

Academic Program: Mechanical Engineering

​The project will use high-speed video cameras to study the motions of drops and bubbles inside high-speed water-flow through a small channel.  Two high-speed cameras will be used to follow the trajectories of the droplets and small bubbles and record their breakup.  The aim of the work is to see how the smallest droplets or bubbles are generated by the turbulent flow-field.  This study is relevant for applications in the petrochemical industry.​​​

DIS/1/0013-01-01

​Fluid Mechanics, Mechanical Engineering or Chemical Engineering

​Perform experiments in the High-Speed Fluids Imaging Laboratory  under the supervision of Sigurdur Thoroddsen. Write a final report describing all the experiments performed and reducing the data.  Write a description of experimental techniques for others to continue the work.

Mechanical Engineering

Physical Sciences and Engineering

Monitoring subsidence due to groundwater pumping in central Arabia

Academic Program: Earth Science and Engineering

Excessive pumping and use of groundwater aquifers in the Middle East is a seriousproblem, leading to aquifer depletion, permanent compaction and shortage of usablewater. One effective way of monitoring the aquifer usage is satellite radar mapping of cm-levelsubsidence due to groundwater pressure decrease in the aquifer systems. In thisproject, we plan to use such satellite radar observations of areas in central Arabia to mapout the extent and magnitude of ongoing subsidence. The results will provide an overviewof the problem of groundwater overuse and may help the authorities to take the necessaryactions.​​​​

BAS/1/1353-01-01

​Earth Science, Environmental science and engineering

The student(s) will learn how to process satellite radar data using Linux/shell based program routines. Theywill also need to learn how to work with the outcome (e.g. in Matlab), display the results, and to providequantitative assessment of the level of subsidence and extent of the groundwater over use problem. Theresults should be summarized in a short report at the end of the internship.

Earth Science and Engineering

Physical Sciences and Engineering

Applications of reduced graphene oxide

Academic Program: Chemical Science

The project will make use of the method developed in the lab for the production of mesoporous reduced graphene oxide. Besides looking into the possibility to scale it up, the student will investigate possible applications for it namely in the environmental and energy-related fields.​​​

BAS/1/1346-01-01

​Chemistry / Materials Science / Physics

​Master the production of reduced graphene oxide​;Optimize the yield of the entire synthesis procedure and develop a strategy for scaled-up production; Evaluate quantitatively the gas and energy storage capacity of the material.

Chemical Science

Physical Sciences and Engineering

Wafer-scale patterned growth of vertically aligned carbon nanotubes

Academic Program: Materials Science & Engineering

​The project aims to optimize the patterned growth of vertically-aligned carbon nanotubes (VA-CNT) on wafers sized up to 4-inches using a plasma-enhanced chemical vapour deposition reactor. The first part will be to optimize the large-area and/or patterned deposition of the metal catalyst. Afterwards, different recipes for the growth of VA-CNT will be explored and, ultimately, a collection of wafers containing from SWCNTs to MWCNTs should be obtained. Characterization of the VA-CNT will be carried out using a collection of tools such as electron microscopy and Raman spectroscopy.​​​​​

BAS/1/1346-01-01

​Materials Science and Engineering / Chemistry / Physics

Si wafers coated with a thin layer of a transition metal active for CNT growth Si wafers coated with a patterned thin layer of a transition metal active for CNT growth Mats of VA-CNTs grown on 4”-wafers Patterned mats of VA-CNTs grown on 4”-wafers One poster or oral communication at a conference Final written report​

Materials Science & Engineering

Physical Sciences and Engineering

Simulations of Large Scale Turbulent Flames using OpenFOAM

Academic Program: Mechanical Engineering

Develop computational fluid dynamics (CFD) simulation code based on OpenFOAM, open-source CFD code modules, to describe large scale turbulent flames relevant to natural fire or industrial combustors. ​​​​​

BAS/1/1316-01-01

​Mechanical/Aerospace/Chemical Engineering, Applied Physics/Mathematics​

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Simulations of Spray and Combustion in Engines

Academic Program: Mechanical Engineering

Develop computational fluid dynamics (CFD) simulation code based on OpenFOAM, open-source CFD code modules, to describe liquid spray injection, atomization, droplet interactions and combustion; and will conduct preliminary simulations for demonstration.​​​​​

BAS/1/1316-01-01

​Mechanical/Aerospace/Chemical Engineering, Applied Physics/Mathematics

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Direct Numerical Simulation of Turbulent Combustion at High Pressures

Academic Program: Mechanical Engineering

Learn the in-house direct numerical simulation code and modify for high pressure and highReynolds number reacting flow problems. Pilot simulations of canonical combustorconfigurations will be conducted as a demonstration of the new capabilities. ​​​​

BAS/1/1316-01-01

Mechanical/Aerospace/Chemical Engineering, Applied Physics/Mathematics

Modified DNS code with specific problem configurations. Pilot simulations and analysis for demonstration.

Mechanical Engineering

Physical Sciences and Engineering

Clean Combustion Research Center

Data Assimilation into large dimensional systems

Academic Program: Earth Science and Engineering

Develop and test efficient data assimilation (such as ensemble Kalman and particle filters and smoothers, 4DVAR, etc) schemes for state and parameters estimation of large dimensional systems. Numerical experiments will be conducted with simplified atmospheric, oceanic, or hydrological models.​

BAS/1/1318-01-01

​Applied Mathematics, Electrical Engineering, Mechanical Engineering, or any related field​

​Report and presentation

Earth Science and Engineering

Physical Sciences and Engineering

Ocean Modelling and remote sensing the Red Sea circulation and ecosystem

Academic Program: Earth Science and Engineering

Study Red Sea circulation and ecosystem using high resolution ocean models simulation, (e.g. MIT ocean general circulation model - MITgcm and European Regional Seas Ecosystem Models - ERSEM), and state-of-the-art remote sensing techniques with available in-situ observations.

BAS/1/1318-01-01

​Physical Oceanography or any related field

​Report and presentation​

Earth Science and Engineering

Physical Sciences and Engineering

Enhancing Weather Downscaling and Forecasting

Academic Program: Earth Science and Engineering

Global weather products can only be computed at coarse resolution, and therefore cannot resolve important sub-grid scale features such as clouds and topography. Downscaling methods are used to compute local weather forecasts at high resolution from the global products. Nudging and Spectral Nudging methods are popular techniques for constraining local models with global products. The goal of the internship is to explore and test more advanced downscaling techniques based on the recently developed continuous data assimilation framework and/or the ensemble Kalman filter.​​​​​

BAS/1/1318-01-01

​Applied Mathematics, Meteorology, or any related field​

Earth Science and Engineering

Physical Sciences and Engineering

Constraining Earth Fluid Motion Models with Satellite Images

Academic Program: Applied Mathematics and Computer Science

Developing exact mathematical models to stimulate and predict oceanic and atmospheric motions is a difficult process because of the complex multi-physical intereactions. Satellite images provide a powerful tool to extract in detail some information at various scales that could be used to reduce the uncertainies in the numerical models. Constraining the models with those images requires introducing some physical knowledge about the studied motion. The goal of this project is to study approaches that would allow to directly contraining and calibrating numerical models with structures extracted from images.​​​​​​

BAS /1/1318-01-01

​​Applied Mathematics, Earth Sciences and Engineering, Electric Engineering or any related field.

​Literature review of images assimilation methods. Explore and study the efficiency of ensemble Kalman flitering methods for images assimilation. Implement and assess performance with numberical test models (e.g. Shallow water)​​

Applied Mathematics and Computer Science

Physical Sciences and Engineering

Quantifying and reducing uncertainties in earth fluid models

Academic Program: Earth Science and Engineering

Earth fluid models are subject to different sources of uncertainties. We will work on developing and implementing Bayesian inference approaches to quantify and reduce uncertainties in these models with focus on applications related to the coastal ocean, e.g. storm surges, tsunamis, oil spill, waves, etc. We envision using statistical and polynomial chaos-based techniques to build surrogate models that can be used to reduce the computational burden of the sampling step in the Bayesian inference.  ​​​​​

BAS/1/1318-01-01

Applied Mathematics, Earth Sciences and Engineering, or any related field

Earth Science and Engineering

Physical Sciences and Engineering