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

University of Exeter; Greater London; On-site; GBP 20,000 - 24,000; Full time

Job summary

The GW4 BioMed3 Doctoral Landscape Programme is offering up to 18 MRC funded studentships across a range of biomedical disciplines, with a start date of October 2027. These four-year studentships provide funding for fees and stipend at the rate set by the UKRI, as well as other research training and support costs, and are available to UK and International students.

This project is in competition for place with the projects across the MRC GW4 BioMed3 Doctoral Landscape Award studentships.

Qualifications

• Funding for UK tuition fees and stipend at UKRI rate.
• Open to UK and International students.
• Start date: October 2027.
• Up to 18 MRC funded studentships across GW4 BioMed3.

Responsibilities

• Conduct biomedical research within the GW4 BioMed3 Doctoral Landscape Programme.
• Engage with training and development activities funded by the programme.
• Contribute to research projects within the discipline areas.

Job description

The GW4 BioMed3 Doctoral Landscape Programme is offering up to 18 MRC funded studentships across a range of biomedical disciplines, with a start date of October 2027.

These four-year studentships provide funding for fees and stipend at the rate set by the UKRI, as well as other research training and support costs, and are available to UK and International students.

This project is in competition for place with the projects across the MRC GW4 BioMed3 Doctoral Landscape Award studentships. There are a total of 18 studentships available across the partnership.

It is well-known that the efficacy of treatments for a specific disease or condition can vary across individuals, so that in settings where multiple treatment options are available, different individuals may require different treatments to obtain the best outcome. Precision medicine methods leverage individual-level characteristics to help optimise treatment choices for individuals. This project will leverage recent advances in Bayesian statistical and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real-world applications in diabetes treatment selection.

These studentships are funded through GW4 BioMed3 MRC Doctoral Landscape Programme and consist of UK tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£21, 805 p.a. for 2026/27, updated each year).

Additional research training and support funding of up to £5,000 per annum is also available.