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source

Changfu Zou

7 months ago

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

Degree Level

Postdoc

Field of study

Machine Learning

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Machine Learning
Electrical Engineering
Chemical Engineering
Materials Science
Robust Control
Transfer Learning
Automatic Control
Lithium-ion Batteries
Optimisation
Data-driven Modeling
Control System

About this position

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.

Funding details

Available

What's required

Applicants must hold a doctoral degree or an equivalent foreign degree by the time of employment decision. Strong written and verbal communication skills in English are mandatory. Preferred qualifications include a doctoral degree in automatic control, electrical engineering, computational materials science, or a related field, and research experience in battery tests, machine learning, data-driven optimization, and/or robust control. Physical presence in Sweden is required for the duration of employment. A valid residence permit must be presented by the start date.

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Professors

Professor at Chalmers University of Technology

University Name
Country flag

Sweden

Research Interests

Control System

Energy Engineering

Electrical Engineering

Materials Science

Machine Learning

Professor at Chalmers University of Technology

University Name
Country flag

Sweden

Research Interests

Automotive Engineering

Energy Engineering

Lithium-ion Batteries

Machine Learning

Robust Control