University College London Offers Fully-Funded PhD on AI-Based Regional Climate Models
University College London (UCL) is offering a fully funded PhD studentship for 2027 focused on artificial intelligence, regional climate modelling, and changes in Earth’s past hydroclimate.
UCL’s fully funded PhD project, “Testing the Ability of AI-Based Regional Models to Capture Hydroclimate Changes of the Geologic Past,” will test whether AI-based climate models can accurately recreate major hydroclimate changes from thousands of years ago.
UCL is offering the studentship through the NERC Centre for Doctoral Training in Understanding Uncertainty to Reduce Climate Risks (UNRISK).
The successful candidate is expected to begin the PhD in October 2027. Applications will close at 1:00 PM GMT on January 13, 2027.
Fully-Funded PhD on AI-Based Regional Climate Models
The research will examine whether AI-powered regional climate models can reproduce known hydroclimate changes from the geologic past.
Scientists use geological records, known as climate proxies, to reconstruct environmental conditions from periods before modern weather observations. However, these records contain uncertainty related to their age, interpretation, and measurement.
The PhD researcher will develop methods to assess these uncertainties and compare geological evidence with climate-model simulations.
The project will use a modified metrological framework developed by the National Physical Laboratory to help measure and represent uncertainty in past climate reconstructions.
Role of Artificial Intelligence
The second stage of the PhD will examine whether higher-resolution climate models provide a better representation of past hydroclimate changes.
The student will analyse paired climate simulations from the National Center for Atmospheric Research (NCAR).
High-resolution climate modelling can require significant computing power. The research will therefore test whether AI-based downscaling can produce similar high-resolution climate information at a lower computational cost.
The project will also use NVIDIA’s AI climate modelling technology to assess whether AI-generated uncertainty estimates can represent the range of climate conditions found in NCAR simulations and geological records.
Who Can Apply
The project is suitable for candidates with a strong quantitative academic background. Relevant disciplines include physics, mathematics, Earth sciences, geography, computer science, and related subjects.
Previous formal training in climate science or data science is not essential for the project. However, applicants should have some experience with scientific programming and strong written and verbal communication skills.
A Master’s degree or relevant professional experience may strengthen an application but is not mandatory for this particular research project.
Applicants must also meet the broader UNRISK academic entry requirements, which generally require at least a UK 2:1 honours degree or an equivalent international qualification in a relevant subject.
Funding Package
The studentship provides full tuition fee coverage and a living stipend at the standard UK Research and Innovation rate. Funding is available for three years and nine months.
The package also includes a £6,000 individual Research Training and Support Grant to support research-related activities.
Students will also benefit from additional cohort-level training funding and opportunities to take part in research placements and specialist training.
International Students Can Apply
The studentship is open to both UK and international applicants. Successful international students can receive full tuition fee coverage under the funding arrangement.
However, the funding does not cover expenses such as UK visa charges or the Immigration Health Surcharge, which overseas students may need to pay separately.
The number of international studentships may also be subject to UKRI funding rules.
Research Environment
The successful student will work within UCL Geography’s Ocean, Atmosphere & Cryosphere Dynamics research group. The project will be supervised by Chris Brierley, while NCAR will participate as a project partner.
The researcher will also have links with the Palaeoclimate Modelling Intercomparison Project (PMIP) community and access to AI climate modelling resources through UCL’s collaboration with NVIDIA.
How to Apply
Applicants should contact the relevant project supervisor before submitting their application.
UNRISK allows candidates to identify up to two research projects during the application process.
Applicants must contact at least one supervisor for each selected project. Candidates must complete the required university and UNRISK application forms and provide information about their academic background, qualifications, research experience, employment, and relevant training.
Applications for the 2027 intake are scheduled to close on January 13, 2027, at 1:00 PM GMT.
Interviews are expected to take place in March 2027, while successful candidates are expected to receive offers later that month.
Find out more details about the Testing the Ability of AI-Based Regional Models to Capture Hydroclimate Changes of the Geologic Past PhD Studentship
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