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University of Exeter

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PhD in Interpretable Probabilistic AI for Quantifying Climate Impacts on Health University of Exeter in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded UNRISK CDT studentship: full university tuition fees, a personal stipend at standard UKRI rates, £6000 individual research and training costs, £5000 cohort-level training, and access to a Flexible Fund for special projects. International applicants must cover student visa costs and the international health surcharge (IHS).

Deadline

Jan 13, 2027

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Country

United Kingdom

University

University of Exeter

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Keywords

Computer Science
Environmental Science
Mathematics
Artificial Intelligence
Mathematical Modeling
Medical Science
Salud Pública
Environmental Epidemiology
Statistics
Salud
Cambio Climático
ML

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About this position

PhD opportunity at the University of Exeter in Interpretable probabilistic AI for quantifying climate impacts on health.

This project sits in Mathematics and Statistics and is focused on using statistics, machine learning, data science, applied statistics, mathematical modelling, environmental science, and environmental health to understand how climate change affects human health across the UK and Europe. The research will work with data and expertise from the Met Office and The Cyprus Institute, and may include a visiting scientist placement at the Met Office.

The project aims to tackle complex questions around compounding environmental exposures such as temperature, air quality, and humidity, and to build interpretable, decision-relevant models that quantify uncertainty and support climate adaptation and policy. Students will develop skills in data analysis, environmental/health data handling, risk mapping, and decision-making under uncertainty.

Supervisors: Dr Theodoros Economou and Dr James Salter.

Funding: This is a fully funded UNRISK CDT studentship covering full university tuition fees, a stipend at standard UKRI rates, research and training costs, cohort training support, and access to a Flexible Fund.

Eligibility: Applicants should have a strong background in statistics and/or machine learning and an interest in environmental epidemiology and climate-health research. Applications are open to UK and international applicants, though international awards are limited by UKRI rules.

Deadline: 2027-01-13.

Funding details

Fully funded UNRISK CDT studentship: full university tuition fees, a personal stipend at standard UKRI rates, £6000 individual research and training costs, £5000 cohort-level training, and access to a Flexible Fund for special projects. International applicants must cover student visa costs and the international health surcharge (IHS).

What's required

Applicants should have a strong background in statistics and/or machine learning, with interest in applying these skills to environmental epidemiology and the climate change-health interface. The project is suitable for students who can work with climate, health, and population data and are comfortable with data analysis and modelling.

How to apply

Apply through the UNRISK website and follow the University of Exeter PhD project application process. Review the project details and funding notes, then submit your application before the deadline.

More information can be found here

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