Changfu Zou

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.

This postdoctoral position at Chalmers University of Technology offers a unique opportunity to advance research in data-driven modelling and optimisation for fast charging of lithium-ion batteries. Hosted by the Division of Systems and Control within the Department of Electrical Engineering, the project addresses critical challenges in battery ageing and safety, focusing on lithium plating and its impact during rapid charging cycles. The research aims to develop safer, faster, and longer-lasting charging strategies for Li-ion cells through two complementary approaches: testing commercial cells under various stress factors to identify optimal fast-charging parameters using data-driven optimization, and designing optimal control strategies on laboratory three-electrode cells with anode potential feedback. Transfer learning and robust control methods will be applied to generalize findings to commercial battery cells. The project is funded by the Swedish Research Council and the Swedish Innovation Agency (Batteries Sweden), ensuring full-time employment for two years with the possibility of a one-year extension. The postdoc will collaborate with leading partners including Uppsala University, Volvo Trucks, ABB, and Husqvarna, and may be eligible to apply for the Marie Skłodowska-Curie Postdoctoral Fellowship in 2026. Chalmers provides a dynamic and inspiring work environment in Gothenburg, with employee benefits such as parental leave, subsidized day care, free schools, and healthcare. The university is committed to gender equality and offers Swedish language courses for international staff. Applicants must hold a doctoral degree or equivalent by the time of employment decision and demonstrate strong written and verbal English skills. Preferred backgrounds include automatic control, electrical engineering, computational materials science, or related fields, with research experience in battery testing, machine learning, data-driven optimization, and robust control. The position requires physical presence in Gothenburg and a valid residence permit at the start date. To apply, submit your application online by April 24, 2026, including a comprehensive CV, publication list, teaching experience summary, and a personal letter outlining your research background and future goals. Incomplete applications and those sent by email will not be considered. References will be requested after the interview. For further information, contact Professors Changfu Zou and Torsten Wik at Chalmers University of Technology.

Chalmers University of Technology is hiring a Postdoc Researcher in Physics-Informed Learning and System Identification for Battery Systems . The opportunity is associated with Professor Changfu Zou at Chalmers University of Technology. The research focus combines physics-informed learning , system identification , and battery systems , making it relevant for candidates with interests in computational modeling, data-driven methods, and energy-related engineering research. This is a postdoctoral opening , so it is aimed at researchers who already hold a PhD or are near completion, depending on the formal vacancy requirements in the full announcement. No funding details, deadline, or eligibility specifics were included in the post excerpt provided. Interested applicants should open the linked LinkedIn vacancy post for the full application instructions and any additional information about the project, supervisor, and submission process.

A postdoctoral position is available in AC Battery Systems at Chalmers University of Technology in Sweden. The post is shared by Professor Changfu Zou , who appears to be the academic contact and likely supervisor for the opening. The research area suggests work connected to battery systems, energy storage, and related electrical engineering topics, with possible overlap in materials science and chemistry. This is a postdoc opening ; no PhD or master's call is indicated in the post. The announcement does not include detailed eligibility criteria, funding terms, or a deadline, so interested candidates should follow the LinkedIn post and contact the poster through the provided profile if needed. Relevant study keywords: battery systems, AC battery systems, energy storage, electrical engineering, materials science, chemistry, electrochemistry.

Chalmers University of Technology is seeking a postdoctoral researcher for a project in physics-informed battery ageing diagnosis and prognosis within the Division of Systems and Control, Department of Electrical Engineering. The position sits at the intersection of battery technology, electrochemistry, modelling, machine learning, and data science, with a clear focus on developing improved methods for diagnosing and predicting lithium-ion battery ageing. The research addresses a major challenge in battery science: internal battery health is difficult to assess accurately from routinely available measurements, especially under realistic and heterogeneous operating conditions. The project aims to create robust, physically interpretable diagnostic and prognostic models using both laboratory data and real-world operational data. You will work with advanced battery-testing facilities and large-scale battery datasets, and validate methods under controlled and practical use conditions. The postdoc will be embedded in an interdisciplinary environment linking automatic control, electrochemistry, and machine learning. The role also includes close collaboration with another postdoctoral researcher working on complementary physics-informed machine learning and system identification methods. Together, the projects are designed to connect methodological advances with real-world battery applications. Applicants must hold a doctoral degree, or an equivalent foreign degree, by the time the hiring decision is made. Strong English communication skills are required, along with the ability to work independently and collaborate effectively in an interdisciplinary research setting. Experience in battery science, computational material science, chemical engineering, electrical engineering, physics engineering, automatic control, or a related field is advantageous. Helpful experience also includes physics-based battery modelling, battery ageing analysis, battery management systems, electrochemical characterisation, battery experiments and ageing studies, machine learning, data analysis, and programming in Python and/or MATLAB. The main responsibilities include conducting research aligned with the project, publishing scientific articles in leading journals and conferences, planning and carrying out battery simulations and some experiments, analysing data, and developing and validating diagnostic and prognostic models. There may also be opportunities to supervise master’s students, co-supervise PhD students, and contribute to teaching at undergraduate and master’s level. The appointment is a temporary full-time position for two years with the possibility of a one-year extension. The expected start date is as soon as possible, subject to visa or work permit processing for applicants outside Sweden. Physical presence throughout the employment is required. Chalmers offers employee benefits and a dynamic research environment in Gothenburg. The university highlights its commitment to equality, diversity, inclusion, and gender balance, and offers Swedish courses for non-native speakers. The application must be written in English and submitted as PDF files via the online system. Required materials include a comprehensive CV and a personal letter explaining your motivation, fit for the role, technical background, achievements, and initial research ideas. The application deadline is 2026-08-16.

Chalmers University of Technology is advertising a postdoctoral position in the Division of Systems and Control, within the Department of Electrical Engineering, in Gothenburg, Sweden. The project sits at the intersection of battery systems, power electronics, and automatic control, with a focus on reconfigurable and AC-native battery architectures for high-power charging infrastructure in electrified transport. The research addresses an important challenge for the growing electrification of passenger vehicles, buses, and heavy-duty transport: how to design battery-supported charging systems that can handle demanding charging profiles, variable power demand, and intensive operation while improving efficiency, durability, and lifecycle cost. The postdoc will work on battery-system modelling, power-electronic architecture analysis, control-oriented methods, and switching/modulation strategies for flexible energy-storage systems. The position is embedded in an interdisciplinary environment at Chalmers, where research and education in electrical engineering, systems and control, and electric power engineering connect with applications in sustainable transport and energy systems. The successful candidate will collaborate with academic and industrial partners in battery technology and electrified transport, and will be expected to produce and present high-quality scientific publications. Applicants must hold a doctoral degree or equivalent foreign degree by the time the employment decision is made, and must demonstrate strong English communication skills together with the ability to conduct independent research and collaborate in a multidisciplinary setting. Strong preparation in electrical engineering, power electronics, automatic control, energy storage, or related areas is particularly relevant. Experience in modeling, simulation, experimental validation, switching converters, real-time control, and programming tools such as MATLAB/Simulink or Python will strengthen an application. Previous battery experience is welcome but not essential, and candidates with strong power electronics and control expertise are especially encouraged to apply. This is a temporary full-time postdoctoral employment for two years. The role requires physical presence throughout the employment period, and a valid residence permit must be presented by the start date. Chalmers offers employee benefits, a strong research environment, and support such as Swedish language courses. The application deadline is 2026-07-31.

Chalmers University of Technology is offering a postdoctoral position in Physics-Informed Machine Learning and System Identification for Battery Systems within the Division of Systems and Control, Department of Electrical Engineering in Gothenburg, Sweden. The project sits at the intersection of automatic control, machine learning, scientific machine learning, optimisation, state estimation, and physical battery modelling. The research aims to develop new physics-informed and data-driven methods for learning, modelling, and predicting complex dynamical behaviour from limited measurements. A key application domain is battery systems, where many important internal processes cannot be directly observed using routinely available data. The work will involve algorithm development, computational methods, theoretical analysis, and validation using simulation, laboratory experiments, and real-world battery data. The postdoc will work in an interdisciplinary environment and collaborate closely with another postdoctoral researcher focused on battery ageing analysis and diagnosis. The project also connects to academic and industrial collaboration opportunities, including Uppsala University and industrial partners such as Volvo Trucks, ABB, and Husqvarna. The position is mainly funded by the Swedish Research Council, and there may also be an opportunity to be hosted by the group to apply for a Marie Skłodowska-Curie Postdoctoral Fellowship in 2026. Applicants must hold a doctoral degree or an equivalent foreign degree by the time the employment decision is made. Strong English communication skills are required. Experience in automatic control, applied mathematics, electrical engineering, computer science, physics, computational science, or a related field is valued, especially with backgrounds in system identification, dynamical systems, machine learning, inverse problems, optimisation, state estimation, uncertainty quantification, or similar areas. Strong programming skills in Python and/or MATLAB and a strong publication record are advantageous. The appointment is a temporary full-time postdoctoral employment for two years with the possibility of a one-year extension. The role requires physical presence throughout the employment. The application must be submitted in English via the online system as PDF files and should include a CV, publication list, relevant coursework, teaching experience if applicable, and a personal letter describing motivation, fit, research experience, technical skills, achievements, and initial scientific ideas. Applications are due by 2026-07-31, and candidates are encouraged to apply early because review and interviews may begin before the deadline.