PhD Studentship: Deciphering Diabetes Heterogeneity via Genetic Decomposition
A four-year MRC-funded PhD to disentangle genetic pathways in diabetes using statistical genetics and computational approaches.
Best for:Best for biomedical researchers with a strong background in genetics, computational biology, or statistical analysis, interested in diabetes research and precision medicine.
Overview
This PhD studentship at the University of Exeter focuses on addressing the complexity of diabetes by separating its genetic underpinnings into distinct biological pathways. The project aims to untangle the contributions of glucose metabolism and red blood cell biology to HbA1c, a key biomarker for diabetes management. Using statistical genetics and computational methods, the research will reveal how these pathways drive disease heterogeneity and long-term complications. The successful candidate will contribute to precision medicine by improving diabetes diagnosis and treatment strategies. The studentship includes full tuition fees, a stipend, and additional research support funding.
What you'll do
- Conduct statistical genetic analyses to disentangle the genetic architecture of glucose metabolism and red blood cell traits in diabetes.
- Develop computational models to separate distinct biological pathways contributing to HbA1c levels.
- Analyze large-scale genomic datasets to uncover mechanisms driving diabetes heterogeneity and complications.
- Collaborate with interdisciplinary teams to integrate findings into clinical and research contexts.
- Present research findings at national and international conferences and publish results in peer-reviewed journals.
- Participate in research training programs and workshops offered by the GW4 BioMed3 Doctoral Landscape Programme.
Requirements
Degree required: A relevant Master’s degree (or equivalent) in Genetics, Biomedical Sciences, Bioinformatics, Statistics, or a related field.
Degree offered: PhD
Language: English; proficiency suitable for academic research and publication (no specific test score mentioned).
Instruction: English
- Strong background in genetics, statistical analysis, or bioinformatics.
- Proficiency in programming languages such as R, Python, or similar for data analysis.
- Experience with genomic data analysis or genome-wide association studies (GWAS).
- Ability to work independently and collaboratively in a research environment.
- Open to UK and international students.
- No specific age or residency restrictions mentioned beyond standard UKRI eligibility criteria.
Funding & terms
How to apply
Deadline: 2026-10-21
Applicants must apply through the University of Exeter’s official funding application portal. The process involves submitting a CV, academic transcripts, a research proposal, and two references. Additional project-specific documentation may be required.
- CV
- Academic transcripts (BSc and MSc)
- Research proposal
- Two reference letters
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