User Researcher jobs in United Kingdom

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85f2e2f44da7

12

12.08.2025

26.09.2025

Purpose of Role

The successful candidate is expected to develop cutting edge deep learning models for multi-scale flow modelling of CO2 in subsurface reservoirs. Two aspects are of special interests (a) pore-to-core scale upscaling (b) upscaling of reactive flow processes at pore-scale. In addition, the successful candidates will contribute to a wide range of AI applications in subsurface flow modelling including (a) stochastic generation of porous media realizations using deep generative models (b) deep learning based property prediction using various architectures (c) Deep learning based proxy modelling with physics based losses and built-in model constrains (d) Efficient coupling of deep learning models to numerical solvers for hybrid CO2 flow modelling. The developed machine learning techniques will be open-sourced and validated across applications, experimental data, and direct numerical simulations generated by the project team.

Key Duties & Responsibilities

The successful candidate will:

• Develop deep learning models for fluid flow in porous media.
• Disseminate research results in peer-reviewed journals and conferences.
• Publish open-source code repositories with techniques, notebooks, blogs, and presentations.
• Participate in project meetings with team members and sponsors.

Essential & Desirable Criteria

• A PhD in computational science & engineering, applied mathematics, physics, or related field (or near completion).
• Experience with computational fluid dynamics using open-source software.
• Strong publication record in high-impact journals.
• Experience with modern software development techniques.
• Excellent communication skills and ability to produce professional reports.