The University of Exeter is advertising a competitive PhD on interpretable probabilistic AI for climate impacts on health. UK and international applicants may compete for funding. The deadline is 13 January 2027. Applicants should consider the research fit and financial conditions together before deciding whether to apply.
Research Focus
The project combines statistics and AI with environmental epidemiology. It examines interacting exposures, uncertainty and decision-relevant interpretation. The research draws on expertise and data from the Met Office and The Cyprus Institute. Read the project description as a starting point for identifying a question that interests you, rather than assuming that every possible method will appear in the eventual thesis.
Location and Academic Team
The university base is Exeter, United Kingdom. The research considers UK and European health impacts. Mathematics and Statistics hosts the advertised opportunity. It forms part of UNRISK. Dr Theodoros Economou and Dr James Salter are named supervisors. The project connects quantitative methods with climate-health research.
Who Can Apply
The project seeks a strong background in statistics or machine learning and an interest in environmental epidemiology. Check the current programme requirements for the precise qualifications and supporting documents needed. A relevant subject or an eligible nationality does not by itself guarantee admission or an award.
Funding and International Conditions
UNRISK offers 15–18 awards across the programme, covering full tuition, a UKRI-rate stipend, £6,000 individual research support and £5,000 cohort training per student. International awards are limited, with visa and Immigration Health Surcharge expenses remaining personal costs. Confirm the applicable stipend and written award terms before making financial commitments.
Exploring the Research Problem
For optional preparation, imagine a model that predicts an outcome reasonably well but is difficult to interpret. Ask what explanation a researcher would need before using its output to support a particular scientific conclusion. Consider how you would distinguish an association in the data from a claim about what would happen after an intervention. This is a hypothetical research-thinking exercise, not a clinical recommendation, an advertised assessment task or a statement about the results this project will produce.
You could extend the example by considering a dataset with incomplete observations and groups that are represented unevenly. Explain which comparison would help reveal whether an apparently strong overall result hides a weakness for part of the sample. State what the analysis could establish and what additional evidence would be needed before drawing a broader conclusion. A careful account of these limits can demonstrate scientific judgement without requiring you to present yourself as an experienced epidemiologist or to claim that a particular model is ready for practical use.
Presenting Evidence of Preparation
If supporting materials are requested, choose a completed quantitative project that shows how you investigated the quality of an analysis. Explain the question, your individual contribution, the method and the evidence used to assess the result. If you worked with sensitive or restricted information, describe your contribution without including private records or material you are not authorised to share. If your experience comes from another application area, explain the transferable statistical or machine-learning skills and distinguish them from subject knowledge you would still need to develop.
If supporting materials are requested, make your individual contribution clear when discussing work completed with other people. Distinguish a class exercise, an unpublished report and a peer-reviewed research output instead of presenting them as equivalent achievements. Explain what your evidence can establish and what remained unresolved, including any limitation that would matter to the conclusion. Adapt these preparation suggestions to the actual application questions, since optional advice does not add requirements to the programme’s document checklist or guarantee a particular assessment outcome.
How to Apply
Use the current programme instructions to establish the submission route and complete supporting-document checklist. Review the exact project title and academic contacts wherever the form asks you to identify your research preference. An informal academic conversation can clarify fit, but it does not replace a formal application or constitute an admission or funding offer.
- View scholarship details and follow the linked institutional application instructions.
- Identify this named project and check the current academic and funding requirements.
- Submit through the specified route by 13 January 2027 and retain confirmation.
Before Submitting
Information was checked on 23 October 2026. Reconfirm the deadline and current terms before submission, particularly where your ability to enrol depends on receiving an international award. Keep a copy of the final form and any written clarification that materially affects your eligibility, financial expectations or decision to accept an offer.