University College London
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PhD in Compound Wind and Rainfall Extremes over Europe: Uncertainty from Climate to Financial Risk University College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Part of the UNRISK CDT offering 15-18 fully funded NERC studentships. Funding covers 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 visa costs and the international health surcharge (IHS); awards for international applicants are limited by UKRI rules.
Deadline
Jan 13, 2027
Country
United Kingdom
University
University College London

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About this position
PhD opportunity at University College London in the Institute for Risk and Disaster Reduction on Compound Wind and Rainfall Extremes over Europe: understanding uncertainties from climate to financial risk.
This project sits at the intersection of climate science, statistics, data science, machine learning, mathematical modelling, and applied statistics. It investigates how compound weather extremes such as winter windstorms coinciding with heavy rainfall create financial losses, and how uncertainty propagates from climate projections to rare-event statistics and ultimately to catastrophe-risk estimates.
The student will work with large climate-model ensembles, multivariate extreme-value methods, and machine-learning emulators to study the frequency, intensity, and clustering of compound wind and rainfall events across Western Europe. The project also examines which uncertainties are reducible through better observations and modelling, and which are fundamentally irreducible. Case studies will include the UK, France, Germany, Belgium, and the Netherlands, with collaboration involving Aon Impact Forecasting.
Funding: This is a fully funded NERC studentship through the UNRISK CDT. It includes full tuition fees, a stipend at standard UKRI rates, research and training costs, cohort training support, and a flexible fund. International applicants are welcome, though visa and health surcharge costs must be covered by the student and awards are limited by UKRI rules.
Eligibility: The ideal applicant has a strong background in physics, meteorology, mathematics, statistics, or another quantitative discipline. Strong Python skills are highly desirable. Experience in climate science, machine learning, or catastrophic modelling is helpful but not required.
Application: Applications are open to UK and international applicants. Check the UNRISK website and the FindAPhD project page for the application route and further instructions.
Funding details
Part of the UNRISK CDT offering 15-18 fully funded NERC studentships. Funding covers 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 visa costs and the international health surcharge (IHS); awards for international applicants are limited by UKRI rules.
What's required
Applicants should have a strong background in physics, meteorology, mathematics, statistics, or related quantitative disciplines. Strong Python programming skills are highly desirable. Experience with statistics, machine learning, climate science, or catastrophic modelling would be advantageous, but prior knowledge is not required; training will be provided. The project suits students interested in interdisciplinary work on climate risk and decision-making.
How to apply
Visit the UNRISK website and apply through the PhD project/programme route. Check the project page and institution website for the application portal and further instructions.
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