Publisher
source

University of East Anglia

PhD Studentship - Predicting and Mitigating Megafires under Climate Change, CASE project with WTW University of East Anglia in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully-funded studentship (fees, stipend, RTSG) for eligible candidates; international fee difference waived for limited number of studentships; relocation, visa, and health surcharge costs not covered.

Deadline

Oct 1, 2026

Country flag

Country

United Kingdom

University

University of East Anglia

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Keywords

Computer Science
Data Science
Machine Learning
Environmental Science
Deep Learning
Mathematics
Geography
Climatology
Spatial Analysis
Earth Science
Python Programming
Fire Safety Engineering
Fire Ecology
Land Management
Earth Observation
R Programming
Climate Dynamics
Mitigation
Statistic

About this position

This PhD project at the University of East Anglia investigates the global risk of megafires—extreme wildfires that pose significant threats to society, ecosystems, and carbon storage. Leveraging recent advances in satellite observations and machine learning, the research aims to fill critical knowledge gaps in understanding the mechanisms that promote or inhibit megafires across different regions. The successful candidate will develop a comprehensive global dataset of individual fires, integrating meteorological and landscape variables to identify and distinguish megafires from typical fires.

Using machine learning techniques, the project will diagnose conditions that make regions prone to megafires, disentangling the roles of weather, landscape, and human factors in fire ignition and suppression. Regional trends in megafire occurrence and weather patterns will be analyzed, with opportunities to contribute to major scientific reports. Training will be provided in programming (Python/R), geospatial data analysis, machine/deep learning, and scientific communication.

Applicants should hold at least a UK equivalent Bachelors (Honours) 2:1 in a numerate, computational, or environmental discipline, with desirable experience in Python or R. English proficiency (IELTS 6.5 overall, 6 in each category) is required. The position is fully funded through an ARIES studentship, covering tuition, a maintenance stipend (£20,780 p.a. for 2025/26), and a research training grant. International applicants may have the fee difference waived, but relocation, visa, and health surcharge costs are not covered.

The start date is 1 October 2026. For more information, visit the supervisor’s research team page.

Funding details

Fully-funded studentship (fees, stipend, RTSG) for eligible candidates; international fee difference waived for limited number of studentships; relocation, visa, and health surcharge costs not covered.

What's required

Applicants must have at least a UK equivalent Bachelors (Honours) 2:1 in a numerate, computational, or environmental subject area. Acceptable first degrees include Mathematics, Statistics, Physics, Economics, Finance, Engineering (Mechanical, Electrical, Civil, etc.), or Data Science. Experience with programming languages such as Python or R for scientific data analysis is desirable. English language requirement: IELTS 6.5 overall, with at least 6 in each category.

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