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Changfu Zou

3 months ago

Postdoc in Physics-informed Battery Ageing Diagnosis and Prognosis Chalmers University of Technology in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Computer Science
Machine Learning
Chemistry
Signal Processing
Electrical Engineering
Chemical Engineering
Materials Science
Electrochemistry
System Identification
Lithium-ion Batteries
Control System
Physics

About this position

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.

Funding details

Available

What's required

A doctoral degree or an equivalent foreign degree is mandatory and must be obtained no later than the time the employment decision is made. Applicants must have strong written and verbal English skills and the ability to independently conduct high-quality research and collaborate effectively in an interdisciplinary environment. Preferred experience includes a doctoral degree in battery science, computational material science, chemical engineering, electrical engineering, physics engineering, automatic control or a related field; research experience in physics-based battery modelling, battery ageing analysis, battery management systems, electrochemical characterisation or related areas; experience in designing and analysing battery experiments including ageing studies and diagnostic measurements; familiarity with machine learning and data analysis; strong programming skills in Python and/or MATLAB; and a strong publication record.

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Professors

Professor at Chalmers University of Technology

University Name
Country flag

Sweden

Research Interests

Control System

Power System

Electrical Engineering

Machine Learning

Materials Science