PhD Studentship: Battery Degradation Modelling and SOX Estimation for EV Applications Oxford Brookes University in United Kingdom

[Bursary of £21,805 per annum. Covers university fees at the home rate only and includes bench fees; international and EU students without Settled Status must cover the difference to international fees. Visas and associated costs are not covered.]

Oxford Brookes University is offering a 3-year, full-time PhD studentship on Battery degradation modelling and SOX estimation for EV applications. The project sits at the intersection of electrical engineering, control, estimation theory, and battery systems, with a strong focus on developing physics-informed, state-based estimation algorithms for lithium-ion batteries in electric vehicle contexts.

The research will be supervised by Prof Shahab Resalati (Director of Studies) and Dr Aydin Azizi. The project is being carried out in collaboration with Jaguar Land Rover, and aims to integrate electrochemical degradation models with advanced estimation techniques such as Kalman filtering and observer-based methods. The goal is to enable real-time prediction of internal battery states and ageing mechanisms while balancing model fidelity, computational efficiency, and robustness under changing operating conditions.

Applicants should ideally hold a Master’s degree or equivalent in Electrical Engineering, Control Engineering, Mechatronics, Robotics, or a closely related discipline with a strong dynamic-systems background. Essential preparation includes state-space modelling, estimation theory, control systems, lithium-ion battery systems, BMS, and familiarity with battery models such as equivalent circuit and electrochemical models. Proficiency in MATLAB and Simulink is required, together with the ability to develop and implement state estimation algorithms for real-time use. The university also seeks candidates with strong analytical, independent research, and communication skills.

Desirable experience includes advanced estimation methods (Extended/Unscented Kalman Filters, particle filters), battery degradation and ageing, SOC/SOH/SOP estimation, reduced-order electrochemical modelling, hybrid physics-based/data-driven approaches, battery testing and parameter identification, automotive systems, embedded BMS constraints, system identification, uncertainty-aware modelling, large datasets, machine learning, and evidence of research capability through a thesis, publications, conference presentations, or industrial work.

Funding is available as a £21,805 annual bursary. The studentship covers university fees at the home rate only and includes bench fees; international students and EU students without Settled Status must pay the difference between home and international tuition rates, and visa costs are not covered. The opportunity is open to home, EU, and international students, subject to the stated funding conditions.

The deadline is listed as 23 September in the headline information, while the detailed description states 23 October 2026; the latter is the explicit closing date in the full posting. Interviews are expected online, and the intended start date is January 2027.

To apply, candidates should contact the studentship team first at [email protected], then submit an application through the Oxford Brookes University direct-application portal. Required documents include a cover letter, CV, details of two referees, degree certificates and transcripts, a passport scan, English language evidence, and funding evidence for international/EU applicants.