At a Glance
- Tasks: Lead machine learning-based weather forecasts for African agriculture and evaluate their effectiveness.
- Company: Join a collaborative project funded by the Gates Foundation, led by the Alan Turing Institute.
- Benefits: Enjoy 42 days of holiday, a generous pension scheme, and discounted gym membership.
- Why this job: Make a real-world impact in climate dynamics while working with international partners.
- Qualifications: Atmospheric science expertise and a passion for tackling weather prediction challenges required.
- Other info: Flexible working arrangements and potential visa sponsorship available.
The predicted salary is between 28800 - 48000 ÂŁ per year.
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.
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.
A significant part of your work, in collaboration with the African groups, will be to understand how to create and evaluate forecasts of highest priority to farmers (such as rainfall onset prediction) from the machine-learning derived products. We aim to understand the predictability of these forecasts as a function of lead time, spatial scale and the controlling physical processes or phenomena. You will also lead on the evaluation of the forecasts according to known physical drivers and constraints, such as tropical wave modes, feedback with the land surface and response to global sea surface temperatures. From these insights into climate dynamics in the machine-learning predictions, we aim to understand drivers of predictability: are there “windows of opportunity” of high predictive skill which may benefit farmers?
Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information please visit: www.gov.uk/skilled-worker-visa.
For research and academic posts, we will consider eligibility under the Global Talent visa. For more information please visit: https://www.gov.uk/global-talent.
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!
If you are looking for a role where you develop real-world impact from your climate dynamics expertise, apply today.
To explore the post further or for any queries you may have, please contact:
Professor Douglas Parker
Email: d.j.parker@leeds.ac.uk #J-18808-Ljbffr
Research Fellow in African Sub-seasonal Weather Prediction employer: University of Leeds
Contact Detail:
University of Leeds Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Fellow in African Sub-seasonal Weather Prediction
✨Tip Number 1
Familiarise yourself with the Cumulus project and its objectives. Understanding the specific challenges faced in African agriculture and how machine learning can address these will help you articulate your passion and knowledge during discussions.
✨Tip Number 2
Network with professionals in the field of atmospheric science and machine learning. Attend relevant conferences or webinars where you can meet potential colleagues or collaborators, as personal connections can often lead to job opportunities.
✨Tip Number 3
Stay updated on the latest research and advancements in sub-seasonal weather prediction and machine learning applications. Being well-informed will not only boost your confidence but also demonstrate your commitment to the field during interviews.
✨Tip Number 4
Prepare to discuss how you would approach the evaluation of forecasts based on physical drivers. Think about specific examples from your past work that showcase your analytical skills and ability to collaborate with diverse teams, especially in an international context.
We think you need these skills to ace Research Fellow in African Sub-seasonal Weather Prediction
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the specific requirements and responsibilities of the Research Fellow position. Highlight your expertise in atmospheric science and machine learning as they relate to the role.
Tailor Your CV: Customise your CV to emphasise relevant experience in weather prediction, climate dynamics, and machine learning. Include specific projects or research that align with the goals of the Cumulus project.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for atmospheric science and your understanding of the challenges in African weather prediction. Mention how your skills can contribute to the success of the Cumulus project and its impact on agriculture.
Highlight Collaborative Experience: Since the role involves collaboration with international partners, emphasise any previous experience working in teams or projects that required cross-cultural communication and cooperation, particularly in research settings.
How to prepare for a job interview at University of Leeds
✨Understand the Project Goals
Familiarise yourself with the Cumulus project and its objectives. Be prepared to discuss how your expertise in atmospheric science and machine learning can contribute to the project's aim of improving weather prediction for African agriculture.
✨Showcase Your Technical Skills
Highlight your experience with machine learning methods and their application in weather forecasting. Be ready to provide examples of past projects where you've successfully implemented similar techniques, especially in relation to climate dynamics.
✨Emphasise Collaboration
Since this role involves working closely with international partners, demonstrate your ability to collaborate effectively. Share experiences where you have worked in diverse teams, particularly in research settings, and how you navigated different perspectives.
✨Prepare Questions About Flexibility
Given the mention of hybrid working arrangements, prepare thoughtful questions about the flexibility of the role. This shows your interest in work-life balance and helps you understand how the team operates in a hybrid environment.