| Location: | Cambridge |
|---|---|
| Salary: | £37,694 to £46,049 |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 6th March 2026 |
|---|---|
| Closes: | 17th April 2026 |
| Job Ref: | LJ49017 |
Department/Location: Department of Materials Science and Metallurgy, West Cambridge
The Department of Materials Science and Metallurgy are seeking a Postdoctoral Research Associate to work on the ADAPT-EAF Programme.
ADAPT-EAF (Accelerating the Development of Automotive and Packaging steel Technology for EAF production) is an EPSRC Prosperity Partnership between the University of Cambridge, WMG at the University of Warwick, Imperial College London, and Tata Steel Research and Innovation Limited. The project addresses one of the central metallurgical challenges associated with transitioning to electric arc furnace (EAF) steelmaking: understanding and controlling the residual elements introduced through scrap-based feedstocks, which can compromise the performance of steels for demanding applications such as automotive body components and steel packaging. ADAPT-EAF will develop a dedicated AI-powered computational platform to predict how different scrap types and compositions affect steel quality and processability. This will be integrated with rapid alloy prototyping and targeted experimental testing to design new automotive and packaging steel grades suited to EAF production. The project supports Tata Steel's programme to commission a state-of-the-art EAF at Port Talbot, a £1.25B joint investment that is expected to reduce UK CO2 emissions by approximately 1.5%.
The postholder will lead the computational research activities within the programme, working in close collaboration with colleagues at WMF Warwick, Imperial College London and Tata Steel. The postholder will need to be comfortable in establishing robust data structures, implementing, refining and developing property sub-models and developing a computational framework in response to experimental data.
The successful candidate will have demonstrated expertise in machine learning and data-driven modelling, particularly probabilistic methods, alongside proficiency in scientific programming (e.g. Python, MATLAB). Knowledge of the steelmaking process would also be desirable.
Funds for this post are initially available for 2 years.
Applicants from academia or industry with relevant backgrounds are welcomed.
For the full overview of the post, alongside essential and desirable criteria, please refer to the linked Further Particulars.
Successful candidates who have not yet received their PhD will be employed on University Grade 5 SP038 (£34,610) as Research Assistants. Upon being awarded their PhD, their salary will be upgraded to Grade 7 041 (£37,694) as Research Associates.
We encourage early applications, as the vacancy may close before the advertised deadline if a sufficient number of suitable applications are received.
Documents in support of applications should include a CV and a research statement.
Should you have any queries, please reach out to Professor Howard Stone and Dr David Collins at: structuralmaterials@msm.cam.ac.uk, with a copy to: jp674@cam.ac.uk and hrmsm@msm.cam.ac.uk Fixed-term: The funds for this post are available for 2 years in the first instance.
To apply online for this vacancy and to view further information about the role, please click on the 'Apply' button above.
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Please quote reference LJ49017 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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