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University of Warwick

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Fully Funded PhD in Physical AI for Battery Management Systems at University of Warwick University of Warwick in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD studentship. For home students (UK nationals and settled status), tuition fees are covered and a tax-free living stipend is paid at the UKRI rate for up to 4 years, including any applicable London weighting. The award also includes £2,000 per year for training and consumables plus access to a Faraday Institution PhD Training Programme valued at approximately £5,000 per year.

Deadline

Sep 25, 2026

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Country

United Kingdom

University

University of Warwick

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Materials Science
Artificial Intelligence
State Estimation
Automatic Control
ML

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About this position

PhD opportunity at the University of Warwick (WMG) in Battery Management Systems (BMS), physical AI, state estimation, modelling, embedded sensing, and intelligent control.

This fully funded studentship explores how an instrumented battery cell with embedded sensing can be combined with in-situ AI algorithms to create next-generation autonomous battery systems. The project focuses on using internal cell data such as temperature, strain, and impedance for monitoring, adaptive self-learning models, early fault prediction, cell-level decision-making, and pack-level optimisation.

The project is based at WMG, University of Warwick, and connects with the Battery Systems Group. The successful candidate will have access to battery manufacturing, testing and HiL labs, HPC resources, real-life data, annual conferences, career fairs, mentorship, internships, and wider training opportunities through the Faraday Institution.

Eligibility: applicants should have a 2:1 or higher Bachelor's degree or Master’s degree (or equivalent) in Control Systems, Physics, Electrical Engineering, or Applied AI. Familiarity with battery systems, state estimation, modelling, and AI algorithms is essential; experience with metrology, sensing, and hardware for AI is desirable.

Funding: for home students (UK nationals and settled status), tuition fees are covered and a tax-free stipend is paid at the UKRI rate for up to 4 years. The award also includes £2,000 per year for training and consumables, plus access to a Faraday Institution PhD Training Programme valued at approximately £5,000 per year.

Application: register your interest via FindAPhD and submit the short Faraday Institution expression of interest form. For enquiries, contact Dr Mona Faraji Niri at [email protected].

Deadline: 25 September 2026.

Funding details

Fully funded PhD studentship. For home students (UK nationals and settled status), tuition fees are covered and a tax-free living stipend is paid at the UKRI rate for up to 4 years, including any applicable London weighting. The award also includes £2,000 per year for training and consumables plus access to a Faraday Institution PhD Training Programme valued at approximately £5,000 per year.

What's required

Applicants need a 2:1 or higher Bachelor's degree or Master’s degree (or international equivalent) in Control Systems, Physics, Electrical Engineering, or Applied AI. Familiarity with battery systems, state estimation, modelling, and AI algorithms is essential. Experience with metrology, sensing, and hardware for AI is desirable.

How to apply

Register your interest through FindAPhD and also submit the short Faraday Institution expression of interest form. The university will respond directly after you enquire. For questions, contact Dr Mona Faraji Niri by email.

More information can be found here

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