Research Fellow in African Sub-seasonal Weather Prediction

Are you an atmospheric scientist looking to apply your expertise to real-world forecasting challenges in Africa?

Machine-learning has the potential to revolutionise weather prediction in Africa, and we are seeking a scientist who understands and enjoys challenges in atmospheric and climate dynamics, weather prediction and predictability. You will take a lead on the deployment and evaluation of a new generation of machine learning-based sub-seasonal weather forecasts for African agriculture.

The Cumulus project is a consortium of UK and African partners funded by the Gates Foundation, which aims to make a breakthrough in the application of machine-learning forecasting methods for West African agriculture. The project is led by the UK’s Alan Turing Institute, with partners in Senegal and Ghana, and all partners will collaborate closely. We will also be part of an over-arching project – Nimbus – linking with US and East African teams and other international specialists.

Within Cumulus, you will lead the application and evaluation of sub-seasonal (2-4 week) forecasts. Other members of the team will be developing innovative machine-learning methods for global sub-seasonal prediction and downscaling for Africa. We aim to get the first models developed rapidly, and you will support work to ensure that the methods can be run, evaluated and improved by partners in African universities and weather services.

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