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University of Exeter

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PhD in Quantifying Uncertainty and Spatial Dependence in Tropical Forest Forecasts for Climate Change Mitigation University of Exeter in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Competition-funded PhD project under 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 cohort-level training, and a Flexible Fund for special projects. International applicants may need to cover visa and international health surcharge costs; awards for international applicants are limited by UKRI rules.

Deadline

Jan 13, 2027

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Country

United Kingdom

University

University of Exeter

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Keywords

Computer Science
Data Science
Environmental Science
Mathematics
Mathematical Modeling
Earth Science
Uncertainty Analysis
Economics
Statistics
ML

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About this position

PhD opportunity at the University of Exeter on quantifying uncertainty and spatial dependence in tropical forest forecasts to support climate change mitigation, conservation planning, and carbon finance.

The project sits within the UNRISK CDT and is supervised by Dr Ben Balmford, Prof Daniel Williamson, and Prof Ben Groom. It focuses on improving statistical and machine-learning methods for forecasting deforestation and regrowth using satellite data, with an emphasis on uncertainty quantification, spatial data, and spatial spillovers.

Research themes include statistics, machine learning, mathematical modelling, data science, environmental science, and applications to forest conservation, climate policy, and conservation finance. The project aims to extend methods such as RSFs, BART, deep kernel learning, variational autoencoders, and neural-network-based spatial models into a portfolio-based decision-support tool.

Funding: fully funded NERC studentship with full tuition, UKRI-rate stipend, research/training costs, and cohort training support. International applicants are welcome, though visa and health surcharge costs may apply and places are limited by UKRI rules.

Eligibility: strong quantitative background in statistics, mathematics, computer science, economics, or a related field; interest in methodological development and environmental applications.

Deadline: 2027-01-13.

Funding details

Competition-funded PhD project under 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 cohort-level training, and a Flexible Fund for special projects. International applicants may need to cover visa and international health surcharge costs; awards for international applicants are limited by UKRI rules.

What's required

Applicants should have a strong background in statistics, mathematics, computer science, economics, or a related quantitative discipline. The project particularly suits students interested in statistical or machine-learning methodology, spatial data, and uncertainty quantification, with motivation to apply these skills to environmental challenges.

How to apply

Review the UNRISK website for full details and application instructions. Submit an application through the project/programme route on the FindAPhD/UNRISK pages. Check eligibility carefully, especially if applying from outside the UK.

More information can be found here

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