PhD Studentship: Advancing Bayesian machine learning methods for precision medicine applications in Type 2 diabetes

Overview

This PhD project at the University of Exeter, based in Clinical and Biomedical Sciences, develops Bayesian machine learning methods for precision medicine in type 2 diabetes. Treatments often work differently from one person to the next, so when several options exist, different individuals may need different treatments to get the best result. Precision medicine uses individual-level characteristics to help choose between them.

The project applies recent advances in Bayesian statistics and machine learning to the main difficulties of building such models from large-scale observational electronic healthcare record data. The models will then be used on real-world questions about selecting diabetes treatments.

What you get

The project is one of up to 18 MRC-funded studentships offered through the GW4 BioMed3 Doctoral Landscape Programme, with a start date of October 2027. The studentships last four years. Funding covers UK tuition fees and a doctoral stipend matching the UK Research Council national minimum, which is 21,805 pounds per year for 2026/27 and is updated annually. Up to 5,000 pounds per year is also available for research training and support costs.

Who can apply

The studentships are open to UK and international students. This project competes for a place with projects across the whole MRC GW4 BioMed3 Doctoral Landscape Award, in which 18 studentships are available across the partnership.

Key dates

The closing date is 21 October 2026, and the studentship begins in October 2027.