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University College London

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PhD in Wildfire Hazard Uncertainty, Urban Response, Adaptation and Insurability University College London 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 visa costs and the international health surcharge; awards for international applicants are limited.

Deadline

Jan 13, 2027

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Country

United Kingdom

University

University College London

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Keywords

Computer Science
Data Science
Environmental Science
Mathematics
Geography
Mathematical Modeling
Climate Science
Civil Engineering
Uncertainty Analysis
Adaptation
Statistics
Physics
ML

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About this position

PhD opportunity at University College London in the Institute for Risk and Disaster Reduction: UNBURNT: UNcertainty from wildfire hazard to BUilt-environment Response, adaptatioN and insurabiliTy.

This project sits within the UNRISK CDT and focuses on wildfire hazard, urban climate science, built-environment response, adaptation, insurability, and uncertainty quantification. The research will combine probabilistic wildfire hazard data, urban microclimate modelling, building-by-building fire spread simulation, machine learning, and scenario analysis to study how uncertainty evolves from hazard to loss in cities.

Supervisors listed are Dr Ting Sun and Dr Roger Cremades. The project links climate science, data science, and decision-making, with industrial and practitioner connections including Climate X, Ortec Finance, and access to fire-service practitioners in London. The project aims to produce an open scenario-engine framework and evidence on which adaptation measures reduce both risk and uncertainty.

Applicant profile: strong preparation in physics, mathematics, engineering, computer science, or quantitative environmental science. Interest in AI, including AI agents, is welcome. Prior fire science knowledge is not required.

Funding: fully funded UNRISK CDT studentship with full tuition, UKRI-rate stipend, research and training costs, cohort training support, and a Flexible Fund. UK and international applicants may apply, though international awards are limited and visa/IHS costs are not covered.

Deadline shown on the listing: 13 January 2027.

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 visa costs and the international health surcharge; awards for international applicants are limited.

What's required

Applicants should have a strong background in physics, mathematics, engineering, computer science, or quantitative environmental science. Interest in artificial intelligence, including AI agents as research tools or representations of human behaviour, is welcome. Prior fire science knowledge is not expected.

How to apply

Apply through the UNRISK website and the FindAPhD listing for this PhD project. Review the project details, funding notes, and eligibility information before submitting an application. International applicants should check visa and IHS costs and the limited number of awards available.

More information can be found here

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