Research Fellow

Coventry University is seeking a motivated and talented Research Fellow to join an industry-led collaborative research project focused on battery intelligence for battery energy storage systems (BESSs). The project will investigate advanced battery testing, modelling, and intelligent state estimation, with an emphasis on physics-guided artificial intelligence (AI).

Fully funded by Innovate UK for 12 months starting February 1st 2027, the project brings together academic expertise and industrial requirements to develop and validate innovative approaches to battery performance assessment, condition monitoring, and state estimation. The successful candidate will be based at Coventry University and work closely with two industry partners to address practical challenges in battery characterisation, operational monitoring, and intelligent battery management system (BMS).

The role will focus on battery testing and data analysis, battery modelling, and the development and validation of AI-enabled algorithms for estimating battery state of charge (SOC) and state of health (SOH). The successful candidate will contribute to experimental investigations, model development, algorithm implementation, and the validation of research outcomes using laboratory measurements and, where available, real-world operational data.

This is an excellent opportunity to undertake applied research at the intersection of battery technologies, artificial intelligence, and energy storage, working directly with industrial partners to translate research advances into practical solutions.

Qualifications Required:
PhD in Electrical Engineering, Electronic Engineering, Control Engineering, Computer Science, Energy Systems, Applied Mathematics, or a closely related discipline; or a relevant bachelor's or master's degree combined with equivalent relevant research or industrial experience.

Person Specification:
A highly motivated and experienced Research Fellow with demonstrable expert knowledge and understanding of battery technologies, particularly lithium-ion batteries, BMS, battery performance, or battery ageing, including experience contributing to the innovation and development of the field. Advanced knowledge of research methods and techniques with demonstrable adherence to all regulations, with the ability to develop research objectives, projects, and proposals for own and joint research.

Research sufficient to write up research and produce excellent, high-quality publications in high profile peer reviewed journals and present at national/international events. Committed to working collaboratively on research development, delivery and dissemination including interdisciplinary or cross-disciplinary research, public engagement, and knowledge exchange.

We are particularly interested in candidates who can combine physics-based understanding with data-driven and AI techniques to develop robust, accurate, and interpretable battery state-estimation methods. Knowledge of lithium iron phosphate (LFP) batteries, including their characteristic flat open-circuit voltage regions and voltage hysteresis, would be advantageous.

Benefits:
- Excellent Employers Pension Contribution
- 30 days Annual leave plus Bank Holidays
- New Holiday Purchase Scheme up to 5 additional days
- Life Assurance 4x Salary
- BUPA Cash Plan
- 50% off Tuition Fees for staff dependants
- CU Reward Scheme – Discounts across a range of High Street/Online Retailers
- Cycle To Work scheme