PhD Studentship: Uncertainty quantification for healthcare models: a route to precision medicine

Overview

Mathematical models serve as vital tools for understanding complex biological and healthcare processes, though ensuring their credibility remains essential for high-stakes clinical decisions. This full-time, fixed-term PhD studentship focuses on uncertainty quantification for healthcare models to advance precision medicine. The researcher will work with a diverse suite of cardiovascular mathematical models in the Department of Mathematics and Statistics at the University of Exeter to build an efficient uncertainty quantification pipeline. The project bridges statistics, cardiovascular physiology, mathematical modelling, and scientific computing.

What you get

The studentship provides coverage of tuition fees alongside a stipend of 21,805 British pounds per annum for the 2026/7 academic year.

Requirements

The research centres on two primary uncertainty quantification focuses. The first area involves emulation and surrogate modelling to accelerate computationally expensive model runs, requiring the student to explore existing techniques and formulate novel, efficient emulation methodologies for large input spaces and multiple related outputs. The second area centres on inverse uncertainty quantification, where the student will calibrate models using real-world observations while explicitly accounting for structural uncertainty and model discrepancy. The ultimate aim is to provide insight into model performance, identify limitations, and deliver defensible predictions to support diagnosis, device selection, and treatment planning in a clinical setting.

Key dates

The closing date for applications is 2026-12-08.