Research Associate in Weather and Climate Modelling with AI

Overview

We have a great opportunity on a NERC-funded Pushing the Frontiers of Environmental Research project to develop complex system modelling and AI techniques to advance our understanding of the UK and Northwest Europe\’s dynamic patterns of atmospheric circulation processes and how they are affected by climate change.

We will develop, adapt and use data-driven modelling techniques, including interpretable machine learning (IML) and nonlinear system identification approaches. In doing so, we will build transparent, interpretable, parsimonious and simulatable (TIPS) models to help identify the causes and impacts of UK and Northwestern Europe\’s atmospheric circulation processes. The results of these models will be compared with parallel experiments carried out using Global Climate Models by the other PDRAs on the project.

Main Duties And Responsibilities

• Use ML/AI techniques and nonlinear system identification approaches (especially NARMAX method) to build transparent, interpretable, parsimonious and simulatable (TIPS) models based on existing and potentially to be available data.
• Identify drivers and causes of North Atlantic atmospheric circulation processes (e.g. observed and measured by the changes in jet stream variability) through the obtained TIPS models.
• Work closely with the other PDRAs on the project to advance the understanding of the implications of the modelled changes in the atmospheric circulation processes on UK and Northwest Europe weather extremes and the resulting impacts for key end-users (environment, energy, wildlife).
• Work to achieve project objectives by conducting research in an appropriate timescale, and working flexibly and both independently and collaboratively.
• Publish results in high quality outlets (high profile conferences and journals), prepare detailed research reports where appropriate (e.g. as formal project deliverables), and communicate results to non-academic or non-specialist audiences as required (e.g. project-wide workshops).
• Attend and contribute to project team meetings, perform project management activities, planning, scheduling, monitoring and reporting on progress of research projects.
• Maintain accurate and complete records of all findings.
• Participate in project meetings and inter/national conferences and convey research findings to a broad audience.
• Carry out administrative roles as required, e.g. to coordinate meetings across various sites.
• As a member of staff, you will be encouraged to make ethical decisions in your role, embedding the University sustainability strategy into your working activities wherever possible.
• Carry out other duties, commensurate with the grade and remit of the post.

Person Specification

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn’t match perfectly with this role\’s criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

Criteria

Essential Or Desirable

• Hold or be close to completing a PhD in Data Driven Modelling, Machine Learning, Applied Mathematics/Statistics, or related engineering and computing fields (or have equivalent experience) – Essential
• Strong background in data-driven modelling of multivariate complex systems including interpretable machine learning – Essential
• Strong experience and skills in modelling and parametric model identification of nonlinear dynamical systems with many inputs including using the NARMAX method – Essential
• Experience of working with climate/weather data – Desirable
• Experience of publishing in peer-reviewed conferences and journals – Essential
• Excellent written and verbal communication skills, including experience writing publications/reports and presenting findings to a range of audiences – Essential
• Ability to work effectively within a team environment including individuals both internal and external to the University – Essential
• Ability to plan own workload and prioritise conflicting deadlines – Essential
• Ability to develop creative approaches to solving complex real-life problems – Essential

Further Information

• Grade 7
• Salary £38,249 – £40,497
• Work arrangement Full-time
• Duration 22 months with a start date in February 2026
• Line manager Dr Leon Wei
• Our website https://www.sheffield.ac.uk/eee
• Contact For informal enquiries about this job contact Dr Hua-Liang (Leon) Wei, Senior Lecturer and Project Lead on w.hualiang@sheffield.ac.uk

What We Offer

• A minimum of 41 days annual leave including bank holiday and closure days (pro rata) with the ability to purchase more.
• Flexible working opportunities, including hybrid working for some roles.
• Generous pension scheme.
• A wide range of discounts and rewards on shopping, eating out and travel.
• A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women’s and Parent’s networks).
• Recognition Awards to reward staff who go above and beyond in their role.
• A commitment to your development; access to learning and mentoring schemes integrated with our Academic Career Pathways.
• A range of generous family-friendly policies
• paid time off for parenting and caring emergencies
• support for those going through the menopause
• paid time off and support for fertility treatment
• and more

More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).

We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.

We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.