Research Fellow in Deep Learning and large-scale Geophysical Modelling

Northumbria University; United Kingdom; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading research institution in the United Kingdom is seeking a Postdoctoral Researcher to focus on developing machine learning emulators for ice-ocean processes. Candidates should have a background in physics or Earth science, and experience in numerical modelling and programming. The role offers collaboration opportunities with international partners and advancement in climate science research. This is a full-time, temporary position starting in February 2026.

Qualifications

• Strong interest in climate science and ice dynamics.
• Prior experience in machine learning is desirable.
• Motivation to contribute to scientific questions about climate change.

Responsibilities

• Develop new approaches based on deep-learning for geophysical models.
• Create fast emulators of large-scale ocean circulation models.
• Collaborate with experts and participate in scientific meetings.

Skills

Machine learning

Numerical modelling

Programming

Ice dynamics

Complex systems

Education

Background in physics, applied mathematics, Earth science, or a related discipline

Job description

Organisation/Company Northumbria University Department Geography and Natural Sciences Research Field Environmental science » Earth science Physics » Other Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Country United Kingdom Application Deadline 30 Nov 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Hours Per Week 37 Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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.

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>
• 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

Sutherland Building, Northumberland Road