Fully Funded PhD in Self-Learning Battery Management Systems for Lithium–Sulfur Batteries Cranfield University in United Kingdom

Fully funded PhD opportunity at Cranfield University in Self-Learning Battery Management Systems (BMS) for Lithium–Sulfur Batteries. The project is hosted in the Advanced Vehicle Engineering Centre (AVEC) and is supervised by Dr Abbas Fotouhi and Prof Daniel Auger.

This research focuses on battery management systems, lithium–sulfur batteries, machine learning, battery modelling, and real-time data analytics. The aim is to develop an intelligent, physics-based, self-learning BMS that can adapt to ageing, changing conditions, and different usage patterns, improving performance, safety, reliability, and lifetime of next-generation Li-S batteries.

The PhD candidate will join Cranfield’s battery research environment and have access to the Battery Lab and experimental facilities, with training provided before lab use. The project is supported by the Faraday Institution and includes a UKRI stipend for 4 years, plus funding towards fees, travel, consumables, and conferences. A bespoke Faraday training programme is also included.

Eligibility: applicants should hold a first or second class UK honours degree or equivalent in a related discipline. Coding, modelling and simulation, machine learning, and battery systems experience are advantageous. The opportunity is open to home students only (UK nationals or those with settled status).

Deadline: 22 July 2026. Reference: CRAN-0089.