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"PDRA to work on the ADAPT-EAF Programme. (Fixed Term)"

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PDRA to work on the ADAPT-EAF Programme. (Fixed Term)

Postdoctoral Research Associate (PDRA)

April 17, 2026

Location

Cambridge

University of Cambridge

Type

Fixed-term

Salary

£34,610 - £37,694 (Grade 5/7 depending on PhD)

Required Qualifications

Machine learning expertise
Data-driven modelling
Probabilistic methods
Python/MATLAB proficiency
Steelmaking knowledge (desirable)

Research Areas

Electric Arc Furnace (EAF) steelmaking
AI-powered computational platform
Scrap-based steel feedstocks
Automotive and packaging steels
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PDRA to work on the ADAPT-EAF Programme. (Fixed Term)

PDRA to work on the ADAPT-EAF Programme. (Fixed Term)

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.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Applicants are asked to upload the following:

  1. A short research statement (maximum 1 page) describing the applicant's past research, future goals, and why the applicant is interested and suitable for this position.
  2. A curriculum vitae.
  3. A publication list.
  4. The contact details of two referees that can provide a letter of recommendation for the applicant.

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.

Apply online

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Frequently Asked Questions

🎓What are the key qualifications for this PDRA role?

The position requires demonstrated expertise in machine learning and data-driven modelling, particularly probabilistic methods, plus proficiency in scientific programming such as Python or MATLAB. Knowledge of steelmaking processes is desirable. See tips for postdoctoral success and postdoc jobs.

💰What is the salary and contract duration?

Salary starts at Grade 5 SP038 (£34,610) for those without PhD, upgrading to Grade 7 041 (£37,694) upon award. The role is fixed-term for 2 years. Explore university salaries for more insights.

📄How do I apply for this University of Cambridge PDRA position?

Upload a CV, 1-page research statement, publication list, and two referees. Quote reference LJ49017. Apply online via the recruitment system. Early applications encouraged. Guidance on resume templates and academic CVs available.

🔬What is the ADAPT-EAF Programme?

ADAPT-EAF is an EPSRC Prosperity Partnership between University of Cambridge, WMG Warwick, Imperial College London, and Tata Steel. It develops an AI-powered platform to predict scrap effects on EAF steelmaking for automotive and packaging steels, supporting Tata's Port Talbot EAF.

Can I apply without a PhD or steelmaking experience?

Applicants without PhD start as Research Assistants at lower grade, upgrading upon award. Steelmaking knowledge is desirable but not essential; focus on machine learning and programming skills. Industry or academia backgrounds welcome. Check research jobs for similar roles.

📧Who should I contact for queries about this postdoc role?

Contact Professor Howard Stone and Dr David Collins at structuralmaterials@msm.cam.ac.uk, copying jp674@cam.ac.uk and hrmsm@msm.cam.ac.uk. Refer to Further Particulars for criteria.
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