Research Fellow in weather forecast postprocessing with Machine Learning - School of Geography,[...]

Position Details

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

Closing date: 26th March 2026

UK and International travel may be required for this role.

Background

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 will advance 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 at BAS. There 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.

Role Summary

• 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

Main Duties

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 weatherforecasts.
• Develop research objectives and proposals for own or joint research, with assistance of a mentor if required
• Contribute to writing bids for research funding
• Apply knowledge in a way which develops new intellectual understanding
• Disseminate research findings for publication, research seminars etc
• Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline
• Contribute to developing new models, techniques and methods
• Undertake management/administration arising from research
• Contribute to Departmental/School research-related activities and research-related administration
• Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader
• Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters
• Provide guidance, as required, to support staff and any students who may be assisting with the research
• Deal with problems that may affect the achievement of research objectives and deadlines
• Promotes equality and values diversity acting as a role model and fostering an inclusive working culture.

Person Specification

• PhD, or close to completion, in a relevant, quantitative field, e.g. meteorology, machine learning, climate science, physics, mathematics, statistics or related fields.
• Evidence of good understanding (or capacity to develop understanding) of statistics and ML.
• Evidence of a good understanding (or capacity to develop understanding) of meteorological processes and numerical weather prediction, and preferably specific knowledge related to monsoon precipitation.
• Experience working with large meteorological datasets.
• Good programming skills in languages such as Python, MATLAB or R.
• Familiarity with UNIX/LINUX.
• High level analytical capability.
• Ability to communicate complex information clearly.
• Ability to assess resource requirements and use resources effectively.
• Understanding of and ability to contribute to broader management/administration processes.
• Contribute to the planning and organising of the research programme and/or specific research project.
• Co-ordinate own work with others to avoid conflict or duplication of effort.
• Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly.

Informal enquiries to Martin Widmann, email: m.widmann@bham.ac.uk

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