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JOB ADVERT : Research Fellow in Machine Learning Accelerated Weather and Climate Modelling


New member
Post Title: Research Fellow in Machine Learning Accelerated Weather and Climate Modelling

SBU/Department: School of Physics, Engineering and Computer Science

FTE: 1 FTE (working 37 hours per week)

Duration of Contract: 36 Month Fixed Term Contract

Salary: UH7 £35,333 - £42,155 per annum depending on skills and experience

Location: College Lane Campus, Hatfield

Main duties and responsibilities

The Research Fellow will help lead a project combining weather and climate modelling with machine learning to develop new techniques to efficiently predict key meteorological parameters at high spatial and temporal resolution. The Fellow will be responsible for running, maintaining and updating relevant software and codes on the University’s Unix/Linux-based high-performance cluster.

The successful candidate will be required to problem-solve day-to-day issues related to the research project and contribute to the development of processes-based approaches including the use of large datasets of model predictions and observations. They must also be able to work well in a team and be prepared to communicate key findings with team-members and stakeholders.

In addition, the Research Fellow will also assist in other activities and projects when required. For example, the preparation of funding proposals and maintenance of the high-performance computing cluster and relevant software.

Skill and experience required

You will have proven experience working in a research environment and experience of presenting research findings such as contributions to conferences and symposia at a local and national level.

You must have experience in one or more of the following areas:

(i) Demonstrable experience of the development and use of advanced high resolution regional scale weather and/or climate models, specifically using WRF.

(ii) Experience of setting up, running and validating Large Eddy Simulations with WRF.

(iii) Understanding of the theory of multiple scale dynamical and climate interactions and process analysis through the combined use of regional and global models.

(iv) Experience in the use of computational programming techniques for atmospheric physics applications e.g. use of languages such as Fortran and Python on Unix platforms, data analysis/visualisation techniques and the ability to maintain codes

(v) Experience in meteorological and climate measurements

(vi) Other experience such as the use of global climate models will also be relevant

(vii) Experience using machine learning techniques, ideally neural networks and their applications

The ability to plan and manage your own activities effectively is essential. You will have good oral and written communication skills in both spoken and written English. Excellent interpersonal and presentation skills are essential.

Qualifications required

You will hold an Undergraduate Honours Degree at a minimum 2:2 (or equivalent) in a relevant discipline (e.g. Physics, Chemistry, Mathematics, Meteorology, Computer Science, Engineering) and a PhD (or equivalent) or close to completion (no more than 3 months prior to viva) in a relevant subject related to meteorological and/or climate modelling and observation with strong computer programming elements based on Unix based cluster systems.

Please view the job description and person specification and the Annex providing further details for a full list of the duties and essential criteria. Please attach a personal statement showing clearly how your skills and experience match the Person Specification.

Contact Details/Informal Enquiries: James Geach,

Closing Date: 22 February 2023

Interview Date: TBC

Reference Number: 048015

Date advert placed: 25 January 2023

Our vision is to transform lives: UH is committed to Equality, Diversity and Inclusion and building a diverse community. We welcome applications from suitably qualified and eligible candidates regardless of their protected characteristics, and recognise there are different ways applicants may achieve the criteria in this document. We offer a range of employee benefits including generous annual leave, flexible location opportunities within the UK, discounted Sports Village memberships and free Active Staff sessions, personal and professional development and family-friendly policies. #GoHerts

Apply online at