Research Associate in Weather and Climate Modelling with AI

University of Sheffield; Sheffield; On-site; GBP 30,000 - 50,000; Full time

Job summary

A prestigious university in the UK seeks a researcher to join an interdisciplinary project focusing on data-driven modelling techniques and atmospheric circulation processes. This role offers the opportunity to enhance research profiles and tackle significant challenges in climate change. The ideal candidate will have a PhD or equivalent experience in a related field, along with expertise in interpretive machine learning and nonlinear system identification.

Benefits

Generous annual leave

Pension scheme

Flexible working opportunities

Wide range of retail discounts

Qualifications

• Expertise in data-driven modelling and nonlinear system identification.
• Experience in interpretable machine learning and model identification.

Responsibilities

• Build models from observations of weather and climate variables.
• Develop skills in multivariate data-driven modelling techniques.
• Collaborate with interdisciplinary teams to solve real-world problems.

Skills

Data-driven modelling

Nonlinear system identification

Interpretable machine learning

Education

PhD or equivalent experience

Job description

Overview

University of Sheffield. We have a great opportunity in the School of Electrical and Electronic Engineering for someone with a passion for research looking to use their skills in data-driven modelling techniques to advance our understanding of UK and Northwestern Europe's atmospheric circulation processes and especially how these might be affected by climate change.

You will join a world-leading, interdisciplinary project team composed of scientists from the Universities of Sheffield, Lincoln, Reading, Newcastle, and several other partner institutions such as the UK Met Office, who will work together to conduct highly-motivated research toward solving challenging real-life problems. Your work on this project will help to enhance our strong international research profile.

Responsibilities

• Build transparent and interpretable models from observations of weather, climate and meteorological variables/signals related to UK and Northwestern Europe’s atmospheric circulation processes.
• Develop skills in multivariate data-driven modelling and nonlinear system identification approaches (especially NARMAX) to construct transparent, interpretable, parsimonious and simulatable (TIPS) models that can help identify the drivers and causes of a complex system with many inputs.
• Work as part of an interdisciplinary project team with other institutions toward solving a significant real world problem; plan your workload and prioritise conflicting priorities.
• Collaborate with partner institutions toward solving challenging real-life problems and enhance the project’s impact.

Qualifications

• Hold a PhD (or hold equivalent experience, or close to completion) in a related subject area.
• Expertise and skills in data-driven modelling, nonlinear system identification and interpretable machine learning.
• Experience in interpretable machine learning (IML) and parametric model identification of nonlinear systems with many inputs.

The School and Environment

The School of Electrical and Electronic Engineering (EEE) belongs to the Faculty of Engineering. We are one of the largest academic communities of engineers in the UK, ranked joint 1st for Research Environment in the latest Research Excellence Framework (REF 2021). Our field (EEE) is highly ranked (QS 2024: 11th in UK; The Guardian 2024: 3rd; The Times Higher 2024: 7th in the UK). We host national institutes and centres, including:
• The National Epitaxy Facility
• The National 6G Radio Systems Facility
• Rolls-Royce Control, Monitoring and Systems Engineering University Technology Centre.

We strive to conduct fundamental research and innovation to address global challenges, as well as support the education of the next generation of engineers. The University of Sheffield is a remarkable and inclusive place to work, and its people are at the heart of everything we do. We value diverse backgrounds, abilities and beliefs that make Sheffield a world-class university.

Benefits

We offer a fantastic range of benefits including a generous annual leave entitlement (with the ability to purchase more), a generous pension scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more. Find out more at www.sheffield.ac.uk/benefits and join us to become part of something special!