Postdoctoral Researcher

Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU; www.mbru.ac.ae) is part of Dubai Health, the first integrated academic health system in the UAE. Dubai Health seeks to strengthen Dubai as a global leader in health care, medical education, research, and scientific innovation, to enhance the capabilities of Dubai's healthcare sector. Dubai Health is managing and operating 54 sites, including 6 government hospitals, 26 ambulatory health centers, 20 medical fitness centers, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), and Al Jalila Foundation.

College of Medicine Dept team at MBRU is seeking applications for the position of Research Fellow.

Job Purpose:

Research Fellow Statistical Genetics & AI (Multi-Ethnic Biobanks, GxE

A post-doctoral position is available to work on the genetics of cardiometabolic traits under the supervision of Dr Sumaya Almansoori (www.mbru.ac.ae) in Mohammed Bin Rashid University of Medicine and Health Sciences in Dubai.

The postholder will work as a member of an international multicenter team to deliver a project on the use of gene-environment interactions towards better understanding and prediction of cardiometabolic diseases in diverse populations.

Responsibilities:

• Opportunity to work on high-impact, multi-ethnic precision health research with direct relevance to the UAE and global communities.
• Access to unique datasets and collaborations across leading international and regional partners.
• Strong authorship opportunities and support for conference participation and professional development.
• A collaborative environment with clear milestones and a focus on translation and real-world impact.

Educational requirements:

PhD (or equivalent experience) in Statistical Genetics, Genetic Epidemiology, Biostatistics, Computational Biology, Bioinformatics, or a related field.

Experience:

Demonstrated experience with large-scale human genetics analyses (e.g., GWAS/QC, ancestry inference/adjustment, meta-analysis, rare variant association).

Strong programming ability in R and/or Python, with experience working in reproducible research environments (Git, documented pipelines).

Solid understanding of study design and statistical inference (confounding, multiple testing, validation strategies).

Evidence of research productivity (e.g., publications, preprints, or substantial analytical contributions).

Please submit your CV and a cover letter outlining your suitability for the role.

Only shortlisted candidates will be invited for an interview.