Obtenez une réponse de cet employeur
Votre CV et votre lettre de motivation, adaptés exactement à ce que l’employeur recherche.
Coventry University invites applications for a Research Fellow to join an industry-led project on battery intelligence for energy storage systems. The role focuses on battery testing, modelling, and AI-based state estimation, with practical validation against laboratory measurements and real‑world data.
You will work within a multidisciplinary team, contribute to experimental investigations, algorithm development, and dissemination of results.
Coventry University is a global Education Group that empowers students and communities to transform their lives and society through teaching, learning, research, and enterprise.
An ambitious and innovative university, our research is designed to have real-world impact on society and tackle global challenges through our 13 challenge-led, interdisciplinary research centres. We enable high performing research teams and future research leaders to thrive and make an impact locally, regionally, nationally, and globally.
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. Based at Coventry University working closely with two industry partners to address practical challenges in battery characterisation, operational monitoring, and intelligent battery management system (BMS).
Focusing 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). You 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.
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.
You will need expertise in lithium-ion batteries, BMS, battery performance and ageing. You will have a strong research track record, including high-quality publications, successful collaboration across multidisciplinary teams, and experience developing research proposals and projects. Advanced knowledge of research methods and regulatory compliance is essential.
Candidates with expertise in combining physics-based battery modelling and AI-driven approaches to develop robust battery state-estimation methods are particularly encouraged to apply. Knowledge of LFP batteries, including voltage hysteresis and flat open-circuit voltage characteristics, would be advantageous.
As a staff member of Coventry University, you will have access to a wide range of industry leading rewards and benefits which includes:
As a global Education Group, equality, diversity, and inclusion are embedded within the fabric of our organisation and are a key focus of our core values. We harness the power and potential of the diverse cultures, backgrounds, abilities, and experiences of our students, colleagues, and partners to create opportunities for all.