About the job

The University of Leeds is inviting applications for the position of Research Fellow in Machine Learning for African Weather Prediction, based at the School of Earth and Environment, with scope for hybrid working. This exciting role is part of the Gates Foundation-funded Cumulus project, a consortium of UK and African partners led by the Alan Turing Institute, aiming to revolutionise weather prediction for West African agriculture. Working closely with teams in Senegal, Ghana, and across East Africa through the umbrella Nimbus project, you will lead the development of machine learning-based “downscaling” methods for sub-seasonal forecasts, particularly using deep learning to transform global-scale predictions into accurate, field-level insights for farmers. You will handle African-specific data sources, optimise foundation codes, and address spatio-temporal uncertainty, ensuring that methods are practical, scalable, and deployable by local universities and weather services. A strong emphasis will be placed on evaluation, benchmarking, and close collaboration with African and international partners. This post is suitable for sponsorship under the Skilled Worker visa route and may also qualify for the Global Talent visa. In return, the University offers a competitive salary of £41,064 to £48,822 per annum, 42 days of annual leave including bank holidays and closure days, generous pension and life assurance contributions, access to wellbeing facilities such as a modern gym and sports complex, professional development opportunities, childcare support, shopping discounts, and flexible working arrangements. This full-time fixed-term contract will run until September 30, 2027, providing a unique opportunity to make a real-world impact through the application of machine learning to climate and weather challenges in Africa.