Research Fellow in Deep Learning and Large-Scale Geophysical Modelling

We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate Change and Effect of Mitigating Solutions, an international collaboration led by the Niels Bohr Institute and funded by the Novo Nordisk Foundation.

About the Role

You will develop new approaches based on deep-learning methodologies to create fast emulators of large-scale geophysical models. 

The specific goal is to develop an emulator of the MIT general ocean circulation model (MITgcm) for a regional configuration of the Southern Ocean to emulate ocean-induced melt rates at the underside of the ice shelves in the Amundsen Sea. Utilising the latest advances in deep-learning, you will create a general framework for emulating ice-shelf melt rates for a range of ocean thermohaline conditions and ice-shelf cavity geometries produced by the MITgcm model in a coupled configuration with a dynamical ice-flow model. The emulator will be constrained by physical principles and capable of producing output fields near-identical to those of a large-scale ocean circulation model, at a fraction of the computational cost. 

Research Environment

You will join Northumbria University’s Future of Ice on Earth research group, one of the largest and most active ice-sheet and ice-ocean modelling communities in the world. You will be assisted by several experts in machine learning including Prof Wai Lok Woo at Northumbria University and Dr Hubert Shum at Durham University. The project provides opportunities to collaborate closely with international partners, participate in scientific project meetings, and present your work at leading conferences and workshops in glaciology, ice-ocean interactions, and deep learning.

About You

We welcome applications from candidates with a strong interest in climate science and ice dynamics. You should have:

• A background in physics, applied mathematics, Earth science, or a related discipline
• Skills in numerical modelling, programming, and handling large datasets
• Prior experience in machine learning is desirable
• Interest in nonlinear dynamics and complex systems
• Motivation to contribute to key scientific questions about climate change and Earth’s future

Further information is within the job description. 

How to Apply?

We welcome applications from the UK and across the world. Visit our web pages for details about Relocation Assistance.

If you would like an informal discussion about the role, please contact Prof Hilmar Gudmundsson (hilmar.gudmundsson@northumbria.ac.uk) or Prof Jan De Rydt (jan.rydt@northumbria.ac.uk).

To apply for this vacancy please click 'Apply Now'.  Your application should include a covering letter and a CV. 

Important dates:

Closing date: 30th November 2025 at 11:59pm

Interview and selection date: w/c 15 December 2025.

Start Date: flexible but aiming at Spring 2026

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