Postdoc in Data-driven Modelling and Optimisation for Fast Charging of Lithium-Ion Batteries Chalmers University of Technology in Sweden

This postdoctoral position at Chalmers University of Technology offers an exciting opportunity to contribute to innovative research at the intersection of battery systems, data-driven modelling, and optimisation. Hosted by the Division of Systems and Control within the Department of Electrical Engineering, the project focuses on developing safer, faster, and longer-lasting charging strategies for lithium-ion batteries. The research addresses key challenges such as lithium plating and battery ageing, aiming to optimise fast-charging parameters through data-driven methods and robust control strategies.

The project is funded by the Swedish Research Council and the Swedish Innovation Agency (Batteries Sweden), ensuring full financial support and access to state-of-the-art facilities. The postdoc will collaborate with leading academic and industrial partners, including Uppsala University, Volvo Trucks, ABB, and Husqvarna. There is also the potential to apply for the prestigious Marie Skłodowska-Curie Postdoctoral Fellowship in 2026 with the support of the host group.

Applicants must hold a doctoral degree (or equivalent) by the time of employment and demonstrate strong English communication skills. Preferred backgrounds include automatic control, electrical engineering, computational materials science, or related fields, with experience in battery testing, machine learning, data-driven optimisation, and/or robust control. The position is full-time for two years, with the possibility of a one-year extension, and requires physical presence in Gothenburg, Sweden. Chalmers offers a dynamic, inclusive work environment with comprehensive employee benefits, support for international staff, and a commitment to gender equality.

To apply, submit your application via the Chalmers online portal by April 24, 2026. Required documents include a CV, publication list, and a personal letter outlining your research experience and future goals. Incomplete applications or those sent by email will not be considered. For further information, contact Professors Changfu Zou or Torsten Wik.