PhD Studentship: Type 2 Diabetes in Lean Individuals
Investigate the causes and treatments of type 2 diabetes in non-overweight individuals through a four-year MRC-funded PhD studentship.
Best for:Best for aspiring doctoral researchers with a background in biomedical sciences, data science, or genetics interested in metabolic disease and large-scale health data analysis.
Overview
The University of Exeter is offering a four-year PhD studentship through the GW4 BioMed3 Doctoral Landscape Programme, focusing on understanding the causes and optimal treatments for type 2 diabetes in lean individuals. The successful candidate will collaborate with multidisciplinary experts in diabetes, data science, and genetics, utilizing large-scale population health datasets. The research aims to decode why lean patients develop apparent type 2 diabetes and how medical care can be tailored for them. The position provides comprehensive funding covering tuition fees and a competitive living stipend alongside research training support.
What you'll do
- Analyze large-scale existing health datasets and genetic studies comprising hundreds of thousands of individuals with diabetes
- Investigate the underlying physiological and genetic causes of type 2 diabetes in non-overweight populations
- Collaborate closely with academic experts across diabetes research, data science, and clinical genetics
- Develop and execute computational or experimental workflows to evaluate potential treatment strategies for lean diabetes patients
- Disseminate research findings through peer-reviewed publications and academic conference presentations
- Participate in required doctoral training activities, workshops, and cohort events provided by the GW4 BioMed3 Programme
Requirements
Degree required: BSc or MSc degree in a relevant discipline such as Biomedical Sciences, Biological Sciences, Computer Science, or Economics
Degree offered: PhD
Language: English
Instruction: English
- Strong academic background in biomedical sciences, data science, genetics, or a related quantitative field
- Demonstrated aptitude for data analysis or handling large-scale population datasets
- Familiarity with research methodologies relating to human health, genetics, or clinical studies
- Strong written and verbal communication skills in English
- Open to UK and International students
Funding & terms
How to apply
Deadline: 2026-10-21
Review the available projects across the GW4 BioMed3 partnership and submit your application through the official university application portal or designated external funding link. Ensure all required academic transcripts, statements, and supporting documents are attached before the closing date.
- CV
- Cover letter
- Academic transcripts
- Reference letters
Contact
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