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University College London

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Fully Funded PhD in AI-Based Regional Models and Hydroclimate Change at University College London University College London in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Competition-funded PhD project within 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; awards for international applicants are limited by UKRI rules.

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
Statistical Analysis
Geography
Mathematical Modeling
Climate Science
Earth Science
Physics
ML

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About this position

PhD opportunity at University College London in the Department of Geography with Prof Chris Brierley, focused on climate science, machine learning, data science, mathematical modelling, and Earth science.

This project asks whether AI-based regional downscaling models can capture hydroclimate changes in the geologic past. You will work with paleoclimate proxy records, uncertainty quantification, climate-model evaluation, and high-resolution simulations from PMIP and NCAR, including experiments such as the last interglacial. The project also explores NVIDIA AI-climate downscaling tools and whether their uncertainty estimates match reconstructions and fine-resolution climate simulations.

Funding: This is a fully funded NERC studentship through the UNRISK CDT. Funding includes full university tuition fees, a stipend at standard UKRI rates, £6000 for individual research and training, £5000 cohort-level training, and access to a Flexible Fund.

Eligibility: Applicants should have a numerate background such as physics, mathematics, Earth sciences, geography, computer science, or a related field. Prior climate or data science training is not required, but scientific programming experience is needed. Strong communication skills are essential, and an MSc or relevant professional experience would be an advantage.

Location: London, United Kingdom.

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

Funding details

Competition-funded PhD project within 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; awards for international applicants are limited by UKRI rules.

What's required

Applicants should have a sufficiently numerate background such as physics, mathematics, Earth sciences, geography, computer science, or a related field. Prior education in climate science or data science is not required but would be helpful. An established interest in the topic is important, along with curiosity to learn across disciplines. Some previous experience with scientific programming is required, and strong oral and written communication skills are essential. Relevant professional experience and/or an MSc would improve competitiveness but is not required.

How to apply

Apply through the UNRISK CDT / FindAPhD application route and review the UNRISK website for full details. Check eligibility carefully, especially if applying from outside the UK, and prepare your academic background, programming experience, and supporting documents before submitting.

More information can be found here

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