Research Officer
| Posting date: | 28 November 2025 |
|---|---|
| Salary: | £39,355 to £45,413 per year |
| Hours: | Full time |
| Closing date: | 05 December 2025 |
| Location: | Swansea, Wales |
| Remote working: | On-site only |
| Company: | Swansea University |
| Job type: | Contract |
| Job reference: | SU01334 |
Summary
We are recruiting a Research Officer to help deliver the EPSRC programme grant REMODEL, advancing parallel mesh generation and geometry representation for industrially relevant, high-fidelity simulations at Exascale. Based at Swansea University, you will play a central part in a multi-institution effort that combines artificial intelligence with computational engineering to accelerate and improve pre-simulation workflows.
You will lead the design, implementation and validation of AI-driven geometry processing methods, developing algorithms and software for automated defeaturing, feature detection and intelligent simplification informed by the governing physics. This will include training and deploying machine-learning models that can recognise and classify geometric features critical to simulation accuracy, enabling the removal or simplification of features that do not affect physical performance. You will integrate these capabilities into existing geometry and meshing workflows, ensuring robustness, scalability and reproducibility across a range of engineering applications. You will manage defined tasks and milestones and collaborate closely with colleagues across the consortium to align interfaces and ensure interoperability. The successful applicant is expected to actively produce peer-reviewed publications arising from their developed techniques.
At Swansea, you’ll join a technically driven, publication-active team known for computational modelling and meshing research, with a strong culture of code quality, open and reproducible practices, and mentoring. You’ll have access to modern development workflows and HPC resources, and opportunities to contribute to shared tooling used across the consortium.
Applicants should demonstrate strong Python programming skills, experience with machine-learning libraries such as TensorFlow or PyTorch, and familiarity with computational engineering workflows using solvers such as ANSYS or OpenFOAM. See the job description for further details.
You will lead the design, implementation and validation of AI-driven geometry processing methods, developing algorithms and software for automated defeaturing, feature detection and intelligent simplification informed by the governing physics. This will include training and deploying machine-learning models that can recognise and classify geometric features critical to simulation accuracy, enabling the removal or simplification of features that do not affect physical performance. You will integrate these capabilities into existing geometry and meshing workflows, ensuring robustness, scalability and reproducibility across a range of engineering applications. You will manage defined tasks and milestones and collaborate closely with colleagues across the consortium to align interfaces and ensure interoperability. The successful applicant is expected to actively produce peer-reviewed publications arising from their developed techniques.
At Swansea, you’ll join a technically driven, publication-active team known for computational modelling and meshing research, with a strong culture of code quality, open and reproducible practices, and mentoring. You’ll have access to modern development workflows and HPC resources, and opportunities to contribute to shared tooling used across the consortium.
Applicants should demonstrate strong Python programming skills, experience with machine-learning libraries such as TensorFlow or PyTorch, and familiarity with computational engineering workflows using solvers such as ANSYS or OpenFOAM. See the job description for further details.