Research Fellow in Machine Learning for African Storm Prediction

University of Leeds
April 03, 2024
Offerd Salary:£37,099 - £44,263
Working address:N/A
Contract Type:Fixed Term (for 24 m
Working Time:Full time
Working type:N/A
Ref info:N/A
Research Fellow in Machine Learning for African Storm Prediction

Salary: Grade 7 (£37,099 - £44,263 p.a. depending on experience)

This role will be based on the university campus, with scope for it to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements.

The University of Leeds is one of the top 75 universities in the world. We have a truly global community, with more than 39,000 students from 170 different countries and over 9,000 staff of 100 different nationalities. Established in 1904, we have a strong tradition of academic excellence, reflected in first-class student education, along with world-leading research that has a real impact around the globe.

Tropical storms are inherently chaotic, on timescales of a few hours, and therefore daily forecasts of rainfall always have uncertainty. For this reason, “nowcasting” – the communication of real-time observations and short- range (0-6 hour) predictions, is vitally needed across the African continent. However, very few people in Africa currently benefit from nowcasting information.

Through the application of innovative meteorological research to harness satellite data, we are already delivering nowcasts of high-impact storms to Tropical Africa. The new methods you create will lead to improved nowcasting information, released in real time on existing online platforms (https: // and https: // saharan-africa/nowcasting/ ) and the FASTA smartphone app being supported by the National Centre for Atmospheric Science (NCAS) at Leeds, and the UK Centre for Ecology and Hydrology (UKCEH). In this way the results of your research will be used to deliver real-time information to users in Africa.

In delivering the real-time nowcasting services, our aim is to provide the capabilities needed for African national weather services and private sector companies to enhance their delivery of weather forecasts and ensure access to high-quality weather information for African populations. We have formal partnerships with a number of African weather services and other organisations. These partners will collaborate in this project, particularly in evaluation and implementation of methods, but also in our support for capacity-building in Africa. Ultimately, better preparedness and informed decision-making using nowcasting information will improve climate resilience and save lives and livelihoods.

The project is led by the UK's National Centre for Atmospheric Science (NCAS) at the University of Leeds and will be a collaborative enterprise between the Schools of Mathematics, Computing and Earth & Environment in Leeds, and the UK Centre for Ecology and Hydrology (UKCEH) in Wallingford. Our collaboration with UKCEH is long-standing and has led to many successful outputs over the years.

What we offer in return

  • 26 days holiday plus approx.16 Bank Holidays/days that the University is closed by custom (including Christmas) – That's 42 days a year!
  • Generous pension scheme plus life assurance– the University contributes 14.5% of salary
  • Health and Wellbeing: Discounted staff membership options at The Edge, our state-of-the-art Campus gym, with a pool, sauna, climbing wall, cycle circuit, and sports halls.
  • Personal Development: Access to courses run by our Organisational Development & Professional Learning team.
  • Access to on-site childcare, shopping discounts and travel schemes are also available.
  • And much more!

    To explore the post further or for any queries you may have, please contact:

    Professor Doug Parker, Science Co-ordinator for NCAS at Leeds

    Email: [email protected]

    Location: Leeds - Main Campus

    Faculty/Service: Faculty of Environment School/Institute: National Centre for Atmospheric Science (NCAS) Category: Research Grade: Grade 7 Salary: £37,099 to £44,263 p.a. (depending on experience) Working Time: 37.5 hours Post Type: Full Time Contract Type: Fixed Term (for 24 months to complete specific time limited work.) Release Date: Wednesday 28 February 2024 Closing Date: Wednesday 03 April 2024 Reference: ENVNC1019 Downloads: Candidate Brief

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