PhD Studentship: Uncertainty quantification for healthcare models: a route to precision medicine
University of Exeter
Mathematical models are important tools for gaining insight into complex processes across biological systems and healthcare. To support high-stakes decisions in a clinical setting using these models, we need to ensure that their predictions are credible. Uncertainty Quantification (UQ) is one of the key principles of model credibility. Throughout this PhD project, the student will have an opportunity to work with a diverse suite of cardiovascular mathematical models to develop an efficient UQ pipeline. Cardiovas...
Mathematical models are important tools for gaining insight into complex processes across biological systems and healthcare. To support high-stakes decisions in a clinical setting using these models, we need to ensure that their predictions are credible. Uncertainty Quantification (UQ) is one of the key principles of model credibility. Throughout this PhD project, the student will have an opportunity to work with a diverse suite of cardiovascular mathematical models to develop an efficient UQ pipeline. Cardiovas...
Opportunity details
Mathematical models are important tools for gaining insight into complex processes across biological systems and healthcare. To support high-stakes decisions in a clinical setting using these models, we need to ensure that their predictions are credible. Uncertainty Quantification (UQ) is one of the key principles of model credibility. Throughout this PhD project, the student will have an opportunity to work with a diverse suite of cardiovascular mathematical models to develop an efficient UQ pipeline. Cardiovascular disease remains the leading cause of death worldwide, and patient-specific models are increasingly proposed to guide diagnosis, device selection and treatment planning. The barrier to clinical adoption is not modelling capability but credibility: regulators and clinicians need to know how far a prediction can be trusted for an individual patient. This project addresses that gap directly, developing UQ methods that make model predictions and their uncertainties defensible. The project sits at the intersection of statistics, cardiovascular physiology, mathematical modelling and scientific computing. Its methodological core emulation, calibration and the treatment of model discrepancy - comes from the UQ field, but the driving questions come from mathematical modelling: which parameters are identifiable from clinical measurements, and what confidence is defensible in a clinical setting. The student will have an opportunity to closely engage with these communities to explore these questions. Within the project, there are two main UQ focusses: Emulation and surrogate modelling: to perform forward and inverse UQ, many runs of mathematical models are required. If we are dealing with a computationally expensive model, it is common to adopt a surrogate model to s...
Eligibility and requirements: Review the official provider page for the current applicant conditions and required documents.
Funding and benefits
Funding eligibility: UK Students, International Students. Funding amount: £21,805 The studentship will provide funding of fees and a stipend of £21,805 per annum for 2026/7..
How to apply
Whilst the overall goal of the PhD is to apply and develop emulation and calibration methodologies for cardiovascular modelling specifically, these will likely be applicable across a wider range of problems, and the project may seek additional partners to apply and test developed methods across further important application areas.
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Source and verification
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Recorded source check: October 27, 2026. A stored check date does not guarantee that every field is complete or still current. Compare the provider, eligibility, funding and deadline with the live official call before applying.
Benefits
Funding eligibility: UK Students, International Students. Funding amount: £21,805 The studentship will provide funding of fees and a stipend of £21,805 per annum for 2026/7..
Eligibility summary
Requirements
Documents required
Language/test requirements
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