Mathematical modelling of haemostatic data to predict clinical and therapeutic outcomes

Project description

This project offers the opportunity to combine mathematical and computational modelling and laboratory work to advance research in haemostasis, by exploring new ways to target anti- and pro-thrombotic therapies in a personalised way. The project would suit a candidate with a background in applied mathematics or a related discipline, with an interest in gaining experience in biological systems, including some guided, hands-on laboratory work, or with a biosciences/biomedical background interested in gaining expertise in modelling and advanced data analytical methods. You would join an existing collaborative network with a strong track record in postgraduate supervision, and the skills and resources to support the training needed. Throughout the studentship, you will acquire valuable technical skills, including data-driven computational modelling, model validation and laboratory techniques such as thrombin generation assays. You will also gain expertise in integrating computational models with experimental data and the machine learning and statistical skills required to analyse large multi-variate datasets. This is an exciting opportunity to acquire cross-disciplinary skills, alongside insights into a wide range of clinical conditions including diabetes and inherited bleeding disorders. 

This project is part of the AIM Doctoral Training Programme which has a range of exciting and diverse PhD projects at our 3 partner University institutions of Birmingham, Leicester and Nottingham which are now open for application for a September 2026 start.  Further details on how to apply and criteria for funding can be found here: https://more.bham.ac.uk/mrc-aim/phd-opportunities/

Deadline for application to AIM DTC is midday (GMT) on 09 January 2026.