Publisher
source

University of Exeter

Just Landed

PhD in Uncertainty in Risk Modelling of European Windstorms, East Atlantic Pattern, and History Matching University of Exeter in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Part of the UNRISK CDT. Offers 15-18 fully funded NERC studentships covering full university tuition fees, a personal stipend at standard UKRI rates, £6000 individual research and training costs, £5000 per student of cohort-level training, and a Flexible Fund for special projects. International applicants must cover student visa costs and the international health surcharge (IHS).

Deadline

Jan 13, 2027

Country flag

Country

United Kingdom

University

University of Exeter

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

Apply for this position

Keywords

Computer Science
Data Science
Environmental Science
Mathematics
Statistical Analysis
Mathematical Modeling
Climatology
Climate Science
Earth Science
Uncertainty Analysis
Catastrophe Modeling
Econometric
Statistics
Environmental Physics
Physics
ML

Suggested positions

About this position

PhD opportunity at the University of Exeter in Statistics, Climate Science, Data Science, Meteorology, Environmental Physics, and Mathematical Modelling.

This project, supervised by Prof David Stephenson and Dr Matthew Priestley, focuses on understanding uncertainty in risk modelling of European windstorms, with particular attention to the East Atlantic Pattern, extreme wind gusts, climate variability, and history matching / uncertainty quantification in catastrophe models.

The research has two main themes: (1) how the East Atlantic Pattern influences local windstorm risk hotspots in Western Europe and how this pattern may change in the future under climate change and possible Atlantic Meridional Overturning Circulation slowdown; and (2) how to improve catastrophe-model loss simulations using rigorous uncertainty quantification methods such as emulation, history matching, and importance resampling.

Applicants should have an undergraduate degree in a quantitative subject such as statistics, mathematics, data science, computer science, physics, or climate science. Strong ability to develop advanced statistical methods and work with large meteorological datasets is important, and an interest in weather and climate science is desirable.

This is a fully funded PhD within the UNRISK CDT, with full university tuition fees, a stipend at standard UKRI rates, £6000 for individual research and training costs, £5000 per student for cohort-level training, and access to a Flexible Fund for special projects.

Applications are open to UK and international applicants, although international awards are limited by UKRI rules. International applicants should note they must cover visa and international health surcharge costs.

The listing is for a PhD project at the University of Exeter, United Kingdom. The deadline shown on the page is 13 January 2027.

Funding details

Part of the UNRISK CDT. Offers 15-18 fully funded NERC studentships covering full university tuition fees, a personal stipend at standard UKRI rates, £6000 individual research and training costs, £5000 per student of cohort-level training, and a Flexible Fund for special projects. International applicants must cover student visa costs and the international health surcharge (IHS).

What's required

An undergraduate degree in a quantitative subject such as statistics, mathematics, data science, computer science, physics, or climate science is desirable. Applicants should be able to develop advanced statistical methods and apply them to large meteorological data sets, and an interest in weather and climate science would be beneficial.

How to apply

Apply through the UNRISK website and the FindAPhD listing. Review the project details and submit an application via the programme/application page.

More information can be found here

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?