Research Fellow in weather forecast postprocessing Machine Learning - School of Geography

Research Fellow in weather forecast postprocessing with Machine Learning - School of Geography, Earth and Environmental Sciences - 106116 - Grade 7

United Kingdom

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School of Geography, Earth and Environmental Sciences

Location:

University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £36,130 to £45,413 with potential progression once in post to £48,149

Grade: 7

Full Time, Fixed Term contract up to March 2028

UK and International travel may be required for this role.

The School of Geography, Earth and Environmental Sciences at the University of Birmingham (UoB, UK) is offering a fixed-term postdoctoral Research Fellow (RF) position for one year with a possible extension for one more year. The starting date is November or December 2025.

This post willadvance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop ML methods for postprocessing numerical ensemble weather forecasts over India to improve the skill of precipitation predictions and to generate hydrological forecasts.

The RF will be part of a research environment with strong ML activities. The post is mainly part of the project ‘HEavy Precipitation forecast Post-processing over India with Machine Learning’ (HEPPI-ML), which is funded through the ‘Weather and Climate Science for Service Partnership ’ (WCSSP) programme. It is also linked to the National Institute for Health and Care Research (NIHR) project ‘Improving primary health care for patients with non-communicable diseases during severe flooding in India’, and to several ML-based projects at the British Antarctic Survey (BAS).

There are also strong connections to the Institute for Data and Artificial Intelligence (IDAI) at UoB.

The researcher will work with Dr. Martin Widmann, Dr. Ruth Geen and Prof. Gregor Leckebusch at UoB, and Dr. Andrew Orr re will be close collaboration with the Indian National Centre for Medium Range Weather Forecasting and the UK Met Office, including project meetings in India and visits to the UK Met Office. HEPPI-ML is one out of several WCSSP-India projects and joint meetings will provide an opportunity for further networking.

The successful candidate will hold a PhD, or be very close to completion, in ML, statistics, meteorology, climate science, physics, or related fields. He/she will have substantial experience with ML, or with weather forecasting models. Essential programming skills are UNIX/LINUX, and programming languages such as Python, R or MATLAB.

• Implement and test different ML architectures for postprocessing precipitation forecasts over India.
• Determine how to maximise information extracted from the raw forecasts and how to optimise postprocessing skill for heavy precipitation.
• Develop ML methods to predict hydrological variables from the weather forecasts.
• Publish the results in high-quality journals and present them at conferences.
• Contribute to generating funding

The responsibilities may include some but not all of the responsibilities outlined below.

• Implement and test different Artificial Neural Network (ANN) architectures, such as convolutional and encoder-decoder ANNs, for postprocessing ensemble precipitation forecasts over India from the National Centre for Medium Range Weather Forecasting (NCMRWF) global ensemble prediction system (NEPS-G).
• Develop innovative specifications of input and output of postprocessing that account for the stochastic nature of precipitation and for systematic location errors in the original forecasts.
• Apply Interpretable AI concepts to make the postprocessing transparent and to improve the understanding of processes during heavy precipitation events over India.
• Implement the ML postprocessing methods on high performance computing systems in a way that is suitable for operational use.
• Implement and test different ML architectures, such as convolutional and encoders-decoder ANNs for predicting flooding in Bihar and Kerala from the NEPS-G ensemble weather forecasts.
• Develop research objectives and proposals for own or joint research, with assistance…