PhD Studentship: Robust and scalable methods for hierarchical models in environmental epidemiology, funded PhD in Mathematics. Ref: 5458

Location: Mathematics and Statistics, Streatham Campus, Exeter

The University of Exeter’s Department of Mathematics and Statistics is inviting applications for a PhD studentship fully-funded by the faculty of Environment, Science and Economy to commence on 28 April 2025 or as soon as possible thereafter. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £19,237 for 3.5 years full-time, or pro rata for part-time study.  The student would be based in Statistics and Data Science, in the Faculty of Environment, Science and Economy at the Streatham Campus Exeter.

Project Description:

Climate change has been termed a crisis and although meteorologically the changes are well-understood, impacts to humans and the environment are relatively less understood.  Machine learning methods have a key role to play in understanding climate impacts and in particular human health, where the link needs to be estimated from data. Traditionally, statistical approaches in environmental epidemiology have been employed to model the  abundance of weather and climate data and their association to human health data. However, for large scale studies (e.g. globally) there is a lack of scalable and interpretable (probabilistic) machine learning methods with which such data can be modelled, noting that such modelling is key in understanding the epidemiological risks of extreme weather events.

The focus of this project is to understand the limitations of current statistical frameworks for linking environmental hazards with health risks, and to advance the modelling technology by combining ideas from scalable AI methods and classical (statistical) hierarchical approaches, into a framework that can be used to model very large data sets. The aim is to utilise open-source climate and and health data at a global scale and to use the framework to quantify and predict the associated health risks.

The project will benefit from collaboration with the UK Met Office and the Cyprus Institute, drawing on knowhow and data for this project. The student will further benefit from the multi-disciplinary nature of Mathematics and Statistics at Exeter, with expertise in statistics, machine learning, environmental science, epidemiology. In addition, the University of Exeter’s research environment is ideally placed to support this project, with entities such as the Environmental Intelligence network, the Institute for Data Science and Artificial Intelligence and the Joint Center of Excellence for Environmental Intelligence between the University of the Met Office. As such, the project will focus of weather extremes, such as heat-waves, but also on exposure from poor air quality.

This award provides annual funding to cover Home tuition fees and a tax-free stipend.  For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £19,237 per year tax-free stipend.  The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence on 28 April 2025.

International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.

For further information and to apply please click the 'Apply' button, above.

The closing date for applications is midnight on 28^th April 2025.

Advert information