Salary

£37,369 – £45,641 pa

Job Type Contract

Work Pattern Full time

Work Location On-site

Seniority Mid

Education Phd

Posted 5 Nov 2026 (Today)

Benefits Pension provision Generous annual leave Flexible working Professional development and career progression

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Salary

£37,369 – £45,641 pa

Job Type Contract

Work Pattern Full-time

Work Location On-site

Seniority Mid

Education Phd

Posted 5 Nov 2026 (Today)

Benefits Pension provision Generous annual leave Flexible working Professional development and career progression

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Full Time Fixed Term until 31/01/2030 The Faculty of Medicine at the University of Southampton invites applications for a three-year, full-time, fixed-term Research Fellow to join Professor Hanieh Yaghootkar’s interdisciplinary precision-diabetes research programme. Based at University Hospital Southampton, you will investigate the biological mechanisms underlying type 2 diabetes by integrating measures of organ health with large-scale genetic and clinical data.

Working alongside genetic epidemiologists, clinicians and data scientists, you will apply advanced statistical and machine learning approaches to identify distinct diabetes subtypes, investigate their genetic determinants and improve prediction of disease risk and progression. The role As a Research Fellow, You Will:

- Develop and apply machine learning approaches to identify distinct subtypes of type 2 diabetes using measures of liver, pancreas, adipose tissue and skeletal muscle health.
- Characterise the clinical, metabolic and genetic profiles of diabetes subtypes and evaluate their reproducibility across populations.
- Conduct genome-wide association studies (GWAS) of organ-health traits and diabetes subtypes,



and apply Mendelian randomisation to investigate potential causal relationships.
- Develop and evaluate statistical and machine learning models to predict incident type 2 diabetes and disease progression using genetic and clinical data.
- Analyse large-scale population datasets, including UK Biobank, using robust statistical methods and reproducible computational workflows.
- Contribute to high-quality scientific publications, conference presentations and the dissemination of research findings.
- Collaborate with multidisciplinary researchers across genetic epidemiology, genomics, clinical medicine, imaging, statistics and data science.

You will have opportunities to develop your research expertise, contribute to innovative analytical approaches and build your publication record within an internationally collaborative research environment. About You You will have:

- A PhD in in genetic epidemiology, statistical genetics, biostatistics, data science, computational biology or a closely related discipline.
- Experience analysing large-scale genetic, epidemiological or biomedical datasets, ideally including UK Biobank.
- Robust statistical and computational skills, including proficiency in R and/or Python and experience working in Linux-based computing environments.
- Practical experience conducting GWAS and Mendelian randomisation analyses, including appropriate quality control, sensitivity analyses and interpretation.




- Experience applying machine learning, clustering, predictive modelling or other advanced statistical methods to complex biomedical data.
- An understanding of genetic epidemiology and the application of statistical methods to investigate complex disease mechanisms.
- Evidence of high-quality research outputs, including peer-reviewed publications.
- Excellent analytical, organisational and communication skills, with the ability to work independently and collaboratively within multidisciplinary research teams.
- Experience with metabolic disease research would be advantageous.

What We Can Offer At Southampton, you will join a supportive, internationally connected research environment at the forefront of genetic epidemiology, data science and precision medicine. We offer:

- Access to large-scale biomedical datasets, high-performance computing infrastructure and secure analytical environments.
- Opportunities to work at the interface of human genetics, medical imaging, machine learning and metabolic disease research.
- Collaboration with leading researchers across clinical medicine, genomics, epidemiology and computational science.
- Opportunities for high-impact publications, scientific conferences, professional development and career progression.
- A supportive and inclusive working environment committed to equality, diversity and flexible working, including Athena SWAN principles.
- A competitive University benefits package, including pension provision and generous annual leave.

For informal enquiries, contact Professor Hanieh Yaghootkar (). Working At The University Of Southampton: Check out the staff benefits and why you should join us at The University of Southampton.

Further Details:

- and Person Specification

📌 Research Fellow in Genetic Epidemiology and Data Science (Southampton)
🏢 Data Science Jobs UK
📍 Southampton