University of Warwick
Top university
6 days ago
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
Country
United Kingdom
University
University of Warwick

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested positions
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
Ask ApplyKite AI

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.