FOSTER Intern – Computational Fusion Steel Design
- Job Number
- SU01589
- Contract Type
- Fixed Term
- Salary
- £26,338 to £29,179 per annum
- Working Pattern
- Part Time
- Faculty/Directorate
- Faculty of Science and Engineering
- Location
- Bay Campus, Swansea
- Closing Date
- 17 Jun 2026
- Interview Dates
- 1 Jul 2026 - 2 Jul 2026
- Informal Enquiries
-
- Stephen Jones stephen.p.jones@swansea.ac.uk
- Nicholas Lavery n.p.lavery@swansea.ac.uk
About The University
Swansea University is a research-led university that has been making a difference since 1920. The University community thrives on exploration and discovery and offers the right balance of excellent teaching and research, matched by an enviable quality of life.
Our stunning waterfront campuses and multicultural community make us a desirable workplace for colleagues from around the world. Our reward and benefits, and ways of working enable those who join us to have enriching careers, matched by an excellent work-life balance.
About The Role
The MACH1 research group at Swansea University works in close collaboration with UKAEA to develop structural steels for next-generation tokamak reactors, as part of the LIBRTI-funded NEURONE programme. We combine machine learning-driven alloy design with rapid lab-scale prototyping. This 8-week summer internship offers a meaningful opportunity to contribute to that mission. As the Computational Design Intern, you will use established machine learning models and data-driven methods to design optimised variants of novel fusion steels, working alongside a Prototyping intern whose physical samples will validate your designs. The ideal candidate will have some programming experience (Python or MATLAB) and enthusiasm for data-driven materials science. No prior fusion research experience is needed with training provided from day one. Main activities include:
- Collecting, generating, and cleaning materials datasets
- Feature engineering and training machine learning models
- Interpreting outputs to identify candidate alloy compositions
- Producing documented alloy design recommendations
- Characterising microstructures using microscopy
- Assessing alloys through hardness measurements
You will be embedded in our active research group, with direct links to UKAEA and the wider fusion ecosystem, providing genuine insight into career pathways in this rapidly growing sector.
Equality, Diversity & Inclusion
The University is committed to supporting and promoting equality and diversity in all its practices and activities. We aim to establish an inclusive environment and welcome diverse applications from the following protected characteristics: age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race (including colour, nationality, ethnic and national origin), religion or belief, sex, sexual orientation.
As an inclusive and welcoming workplace, we value people for their skills regardless of their background. Applications are welcome in Welsh and will not be treated less favourably than those submitted in English.
Welsh Language Skills
The Welsh language level required for this role is Level 1 - A little. The role holder will be able to pronounce Welsh words, answer the phone in Welsh (good morning/afternoon) and use very basic everyday words and phrases (thank you, please etc.). Level 1 can be reached by completing a 1 hour course.
The University is a proud bilingual institution, our Welsh Language Strategy outlines our aspiration to promote the language and enable our staff to engage with the language as an additional workplace skill and as a gateway to new cultural and social opportunities. Applications are welcome in Welsh and will not be treated less favourably than those submitted in English. Welsh speakers have the right to an interview in Welsh. Applicants for a role where Welsh skills are essential are expected to present their application in Welsh and will be interviewed in Welsh, if shortlisted.
Additional Information
Applications for this role will take the format of a CV submission and cover letter.