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KU Leuven

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PhD Position on Quantitative Evaluation of Battery Cells Using X-ray Computed Tomography KU Leuven in Belgium

Degree Level

PhD

Field of study

Computer Science

Funding

Fully supported PhD position for 4 years.

Deadline

Dec 18, 2026

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Country

Belgium

University

KU Leuven

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Keywords

Computer Science
Mechanical Engineering
Statistical Analysis
Image Processing
Metrology
Statistics
Ct Imaging
Physics
ML

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About this position

KU Leuven is offering a PhD position on quantitative evaluation of battery cells using X-ray computed tomography (XCT) within the Manufacturing Metrology research group in the Department of Mechanical Engineering.

This project focuses on developing a robust data analysis workflow that turns XCT measurement outputs into reliable and interpretable quality metrics for battery cell assessment. The research sits at the intersection of mechanical engineering, X-ray computed tomography, image processing, statistical analysis, machine learning, and computational data analysis.

The group works on manufacturing quality control, 3D coordinate metrology, and XCT, with a strong emphasis on improving measurement speed, reducing errors, and enabling traceable inspection for industrial use. The successful candidate will join a supportive team of research scientists and contribute to the development of methods for battery quality evaluation using advanced imaging and metrology.

Eligibility: Applicants should hold a Master’s degree in Maths, Computer Science, Physics, Engineering, or an equivalent field, and have distinction in the master’s degree. Strong mathematical and computational skills are important, and experience in XCT or instrument calibration is considered an asset. The post also calls for scientific curiosity, analytical ability, good English communication, independence, teamwork, and willingness to support teaching, workshops, and travel for collaboration.

Funding: The PhD is fully supported for 4 years.

Location: Leuven, Belgium.

Application: Submit an academic CV, bachelor’s and master’s degree details, master’s thesis details if applicable, a one-paragraph motivation statement, and two academic references through the online application tool.

Deadline: 18 December 2026, 23:59 CET.

Funding details

Fully supported PhD position for 4 years.

What's required

Applicants must hold a Master's degree in Maths, Computer Science, Physics, Engineering, or an equivalent field, and have distinction in the master's degree. Preferred background includes statistical analysis, image processing and analysis, and machine learning; experience with X-ray computed tomography or instrument calibration is an asset. Candidates should have scientific curiosity, strong mathematical, computational, analytical, and problem-solving skills, the ability to design and implement experiments and analyse measurement results, adequate English communication skills for meetings and publications, flexibility, good time management, ability to work independently and collaboratively, willingness to report progress regularly, help organise workshops and events, engage in teaching assignments, and travel nationally or internationally.

How to apply

Prepare an academic CV, bachelor degree details, master degree details including thesis information if applicable, a one-paragraph motivation statement, and two academic references. Submit the application through the online application tool before the deadline.

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