PhD position on Quantitative evaluation of battery cells using X-ray computed tomography

The Manufacturing Metrology research group of the KU Leuven Department of Mechanical Engineering investigates, develops, optimises and implements measurement solutions for manufacturing quality control. Our expertise covers surface and 3D coordinate metrology using tactile and optical probes as well as X-ray Computed Tomography (XCT). We target Industry 4.0 readiness of measurement solutions by increasing speed, reducing measurement errors, and establishing traceability to realise in-line and in-process capabilities that intelligently feedback inspection results for first-time-right and zero-waste manufacturing. We put our expertise and state-of-the-art equipment at the disposal of manufacturing companies to address complex metrology challenges and to improve manufacturing process understanding and performance.

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Responsibilities

X-ray computed tomography (XCT) is a non-destructive volumetric imaging technology that can image both external and internal structures of parts. The technology has been increasingly used for industrial applications. However, the cost and time consumed to conduct XCT scans are significant for industrial use in the uptake of the technology. Hence, most XCTs are used for research rather than for production purposes.

Recent developments have demonstrated the potential of using XCT to assess the quality of battery cells. However, there is currently no guidance on how to perform dimensional evaluation for such specialised applications, and the impact of systematic influence factors and measurement errors remains largely unknown. This project aims to develop a robust data analysis workflow that converts XCT measurement outputs into reliable, interpretable quality metrics.

As part of this project, you will join a supportive team of research scientists working together to advance battery quality evaluation using XCT. You’ll have the chance to learn new skills, contribute your own ideas, and grow your expertise while shaping your future career path.

Profile

Candidate must

• Hold a Master's degree in Maths, Computer Science, Physics, Engineering, or the equivalent.
• Has distinction in Master degree.
• Be knowledgeable in areas such as statistical analysis, imaging processing and analysis, machine learning
• Experience in X-ray computed tomography or instrument calibration is considered an asset.

Other general requirement

• Has a scientific curiosity and interest in research.
• Has strong mathematical and computational skills.
• Has strong analytical and problem-solving skills.
• Has the necessary skills to design and implement experiments, undertake computational tasks, and analyse measurement results.
• Has adequate English communication skills and can present results competently and comprehensively in research team meetings, conferences and peer-reviewed journal papers.
• Is flexible and has good time management skills.
• Can work independently and have good interactions with the co/supervisors and peers.
• Frequently report the progress of the conducted research to the co/supervisors.
• Is willing to help organise workshops and other events.
• Is willing to engage in teaching assignments.
• Is willing to travel nationally or internationally to visit collaborators to conduct work.

Offer

• The opportunity to pursue a PhD degree that is fully supported for 4 years.
• The project can start immediately following the completion of recruitment.

Interested?

The applicant should provide the following information in the application:

·       An academic CV

·       Bachelor degree (Bachelor specification, University + Country, Year obtained), score

·       Master degree (Master specification, University + Country, Year obtained), Master thesis if any (Title, Year, Supervisor), score

·       A one-paragraph (maximum one page) statement explaining the motivation for applying for this PhD position.

·       Two academic references

For more information please contact Prof. dr. Wenjuan Sun, mail: wenjuan.sun@kuleuven.be or dr. Maryam Ramezani, mail: maryam.ramezani@kuleuven.be.

You can apply for this job no later than December 18, 2026 via the online application tool

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

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