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The way to apply for VSRP internship is to apply via a project below. We have over 100 projects spanning 16 STEM disciplines, and each project has its own 'Apply' button. Each project is 3 - 6 months long and includes airfares, flights, housing, health insurance and a monthly stipend.

You'll be able to work directly with leading researchers in our state-of-the-art laboratories. We're open to applications from motivated students looking to make an impact on the world. If that sounds like you, find a project below that interests you and continue your journey at KAUST!

New research projects have been added in the following areas:

Cybersecurity
Environmental Science and Engineering
Earth Science and Engineering
Computer Science
Applied Mathematics and Computational Science

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CURRENT PROJECTS

Statistical and machine learning methods for health and environmental applications.

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Project Description

The student will work on the development of statistical and machine learning methods for health and environmental applications. The topic is flexible and potential research areas include disease mapping, early detection of disease outbreaks, air pollution modeling, forest fires prediction, integration of misaligned spatial and spatio-temporal data, and the development of R packages for data analysis and visualization. Examples of research projects can be found at https://www.paulamoraga.com/research

Program - Statistics

Division - Computer, Electrical and Mathematical Sciences and Engineering

Faculty Lab Link - https://www.paulamoraga.com

Field of Study - statistics, mathematics, computer science

About the
Researcher

Paula Moraga

Assistant Professor, Statistics and Principal Investigator, Geospatial Statistics and Health Surveillance

Paula Moraga received her Ph.D. in Mathematics from the University of Valencia, and her Master's in Biostatistics from Harvard University. Prior to KAUST, she was appointed to academic statistics positions at Lancaster University, Harvard School of Public Health, London School of Hygiene & Tropical Medicine, Queensland University of Technology and University of Bath.

Paula's research focuses on the development of innovative statistical methods and computational tools for geospatial data analysis and health surveillance including methods to understand geographic and temporal patterns of diseases, assess their relationship with potential risk factors, detect clusters, and evaluate the impact of interventions. She is also interested in the development of statistical software including R packages and interactive visualization applications for reproducible research and communication.

Paula has published extensively in leading journals and is the author of the book 'Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny' (2019, Chapman & Hall/CRC) (https://www.paulamoraga.com/book-geospatial/).

Desired Project Deliverables

The student will work on the development of statistical and machine learning methods for health and environmental applications. The topic is flexible and potential research areas include disease mapping, early detection of disease outbreaks, air pollution modeling, forest fires prediction, integration of misaligned spatial and spatio-temporal data, and the development of R packages for data analysis and visualization. Examples of research projects can be found at https://www.paulamoraga.com/research