Postdoctoral Research Fellow in AI-Based Battery Health Optimisation

Develop AI-driven digital twin frameworks for battery energy storage systems in mission-critical data centres.

Best for:Best for postdoctoral researchers with expertise in AI/ML, digital twin technologies, and energy systems, seeking to contribute to sustainable energy solutions in data centre environments.

University of Exeter · Exeter, United Kingdom · R2 · Recognised researcher

More professors at University of Exeter

AI-based battery health optimisationDigital twin frameworksStationary battery energy storage systemsEnergy systems modellingMission-critical data centre environments

This is a postdoc position — not a PhD studentship.

Deadline

Oct 29, 2026

15 days

Funding

Salaried

£44.4k–£54.4k/yr

Start date

2026-11-01

Full-time

Location

Exeter

United Kingdom

Overview

This postdoctoral position at the University of Exeter focuses on advancing AI-based battery health optimisation for stationary battery energy storage systems (BESS) in data centres. Funded by Innovate UK, the role involves creating a digital twin framework to enhance energy efficiency and reliability in mission-critical environments. The successful candidate will contribute to cutting-edge research, collaborate with interdisciplinary teams, and develop methodologies for AI-driven energy system modelling. The position is ideal for researchers with expertise in AI, machine learning, and energy systems, offering a dynamic environment to drive innovation in sustainable energy technologies.

AI for energy systemsDigital twin technologyBattery energy storage systemsMachine learning in energyEnergy optimisationData centre energy efficiencyInnovate UK funded researchPostdoctoral research fellowship

What you'll do

Develop research objectives, projects, and proposals for AI-driven battery health optimisation frameworks.
Design and implement AI/ML models for digital twin simulations of battery energy storage systems.
Collaborate with interdisciplinary teams to integrate energy systems with data centre environments.
Present research findings at conferences and academic events.
Identify funding opportunities and contribute to securing research grants.
Supervise junior researchers and lead team projects as required.

Requirements

Degree required: PhD in Computer Science, Electrical Engineering, Energy Systems, or a related field, or equivalent professional experience.

Language: English; proficiency sufficient for academic research and collaboration

Instruction: English

Publications: Strong publication record in AI/ML or energy systems research.

Required skills

Proven expertise in applying AI and machine learning to energy systems.
Strong background in digital twin technology and BESS modelling.
Experience integrating energy systems with data centre environments.
Proficiency in Python for programming and data analysis.
Ability to develop research methodologies and programmes independently.

Nice to have

Experience with large-scale energy system simulations.Familiarity with cloud-based or distributed computing platforms.Publications in top-tier AI or energy-related conferences/journals.

Eligibility

No specific nationality or residency restrictions mentioned.
No age or prior experience caps explicitly stated.

Funding & terms

Type

Salaried

Amount

£44.4k–£54.4k/yr

Duration

12 months

Programme

Innovate UK

How to apply

Deadline: 2026-10-29

Applicants must submit their CV, cover letter, and research statement through the University of Exeter’s careers portal. Ensure you read the Job Description and Person Specification for full details. Contact Prof Zhong Fan at z.fan@exeter.ac.uk for further information.

Documents required