Research Fellow, Battery (Degradation) Data Curation and Modelling (111411-0326)

Informal Queries

• For informal queries, please contact Mona Faraji Niri (Associate Professor) at Mona.faraji-niri@warwick.ac.uk

Flexible Working

• We will consider applications for employment on a part-time or other flexible working basis (e.g. job share), despite the position being advertised as full-time.

In WMG, we are undertaking research into how traditional Li-ion battery cell design can be optimised through the application of systems engineering, component modelling and data science. Creating new models and predictive tools to improve battery performance, lifetime and safety.

RaRR is a new project commenced in WMG in October 2025, funded by EPSRC and HVMC, with a focus on second-life battery degradation understanding, especially for micro-mobility systems. It also looks at building the capability of management of large volumes of multimodal data by designing and validating efficient and scalable data collection, curation, usage (e.g. for AI) and sharing strategies applicable to R&D environments such as WMG.

Therefore, the Battery Modelling team in WMG seeks a postdoctoral researcher to develop a data capture, storage and reuse strategy, as well as highly accurate and transferable RUL/SoH models for batteries from segregated sources and varying quality at large scale. The candidate will also lead the validation of the methodology's performance using real data.

The ideal candidate blends data analytics and big data management, AI modelling and validation skills, and is comfortable engaging with academia, industry partners, and software teams.

About You

You will need a PhD (or be near submission) in a relevant discipline (could be Electrical/Power/Energy Systems, Control Engineering, Renewable Systems Engineering), along with excellent computing and programming skills in multiple languages and environments. You will also need a problem-solving ability to manage and analyse manufacturing datasets and the ability to publish high-quality academic outputs.

You are expected to have proven experience in developing and applying predictive deep-learning models for data-driven analysis and forecasting tasks. Also have familiarity with emerging agentic AI solutions and their potential for autonomous decision-making and intelligent system orchestration. Familiarity with battery-related datasets across multiple scales and data types is preferred, and the ability to design user interfaces and dashboards is expected.

CLOSING DEADLINE: Sunday 29th March 2026 at 11:55pm (UK Time)

Full details of the duties and selection criteria for this role can be found in the vacancy advert on the University of Warwick's jobs pages. You will be routed to this when you click on the 'Apply' button.

£35,608 to £46,049 per annum

You will need a PhD (or be near submission) in a relevant discipline (could be Electrical/Power/Energy Systems, Control Engineering, Renewable Systems Engineering), along with excellent computing and programming skills in multiple languages and environments. You will also need a problem-solving ability to manage and analyse manufacturing datasets and the ability to publish high-quality academic outputs.

You are expected to have proven experience in developing and applying predictive deep-learning models for data-driven analysis and forecasting tasks. Also have familiarity with emerging agentic AI solutions and their potential for autonomous decision-making and intelligent system orchestration. Familiarity with battery-related datasets across multiple scales and data types is preferred, and the ability to design user interfaces and dashboards is expected.