Access to Frontier AI Models & High-Performance Computing: Instead of only using traditional and resource-heavy physical models, you will work with the latest AI Numerical Weather Prediction (NWP) emulators like ECMWF’s AIFS, ai2’s ACE, and HiRO-ACE. This hands-on experience with fast, high-resolution (down to 3 km) machine learning models is changing the way weather and climate are forecasted. 

Direct Synergies with Major Research Flagships (UK Met Office & AIMIP): This project connects directly with leading national and international climate efforts, including the AI4Climate AI Downscaling flagship and the AI Model Intercomparison Project (AIMIP). You will work alongside expert teams at the UK Met Office (UKMO) and the National Centre for Earth Observation (NCEO), giving you valuable networking, mentorship, and chances to publish impactful work. 

The ability to customise your PhD (comparing model development with policy translation): This project allows you to shape your research to match your career goals in your final years. If you choose the Tech/Data Science Track, you can focus on developing algorithms, improving model architecture, and applying advanced machine learning methods to handle unusual or extreme cases. With the UKRI Policy Internships programme, you can use your research on hazard risks to help shape real adaptation policies. This opens doors to careers in government, NGOs, and international climate agencies. 

Interdisciplinary project that directly addresses a major gap in observations of the Earth 

Learn optimisation methods that underpin modern AI and forecasting to study the land, sea, and atmosphere 

Work at the cutting edge of research into aerosol-cloud and land-sea interactions 

Have you ever wondered whether ancient Mars had a habitat that could sustain life? Early Earth provides clues about the conditions on Mars that may have supported simple organisms. This project will transfer state-of-the-art methods for modelling the Earth Climate system to explore Mars’s ancient past 3.5-3.8 Ga.

Starting in the present, you will learn how to model planetary systems within a modern energy balance framework, adding other components (e.g. a carbon cycle) as needed. You will then use data from Mars Science Laboratory to refine and test your model.

Based at Space Park Leicester, you will be part of a cross-disciplinary team working across the Water and Climate Research Lab and the Mars Science Laboratory mission. You will have access to new Curiosity Rover data, such as ancient atmospheric CO2 abundances based on crustal carbonate abundances. With co-supervisors based at Space Park Leicester, NCEO, Open University and the University of Edinburgh, you will work with UK leading experts across remote sensing, atmospheric and climate cycle modelling, and Earth and Mars science.