Wenjuan Sun
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Postdoc Position on Efficient and Reliable XCT for Industrial Applications KU Leuven in Belgium
Degree Level
Postdoc
Field of study
Signal Processing
Funding
Available
Deadline
Apr 30, 2026
Country
Belgium
University
KU Leuven

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About this position
The Manufacturing Metrology research group at the Department of Mechanical Engineering, KU Leuven, invites applications for a fully funded postdoctoral position focused on efficient and reliable X-ray Computed Tomography (XCT) for industrial applications. The group is renowned for its expertise in surface and 3D coordinate metrology, utilizing tactile and optical probes as well as advanced XCT systems to address complex manufacturing quality control challenges. The research aims to advance Industry 4.0 readiness by developing high-speed, accurate, and traceable measurement solutions that enable in-line and in-process inspection for zero-waste manufacturing.
This project centers on leveraging fast detection XCT systems to expand the range and speed of industrial XCT applications. The successful candidate will develop and optimize scanning strategies and image reconstruction methods tailored to diverse object geometries and materials. The work will include systematic error modeling, optimization of scanning conditions, and comprehensive evaluation of dimensional and structural data. A full data analysis workflow will be established to quantify XCT-based measurements, supporting industrial process improvement and quality assurance.
The position is fully funded for two years, with the possibility of extension, and offers a competitive salary and standard KU Leuven employment benefits. The earliest possible start date is June 2026. The postdoc will join a collaborative team, contribute original research ideas, and have opportunities to participate in teaching, workshops, and international collaborations.
Applicants must hold a PhD in engineering, mathematics, or a closely related field. Desired skills include numerical data analysis, statistical analysis, image processing, machine learning, and experience with XCT error modeling. Strong English communication, teamwork, and problem-solving abilities are essential. Application materials include an academic CV, degree certificates and transcripts, a motivation statement, and two academic references. The application deadline is April 30, 2026, but early applications are encouraged as the position may be filled sooner. For further information, contact Prof. Wenjuan Sun at [email protected].
KU Leuven is committed to diversity, inclusion, and equal opportunity, providing a supportive and respectful research environment. For more details on working conditions, visit the KU Leuven jobsite.
Funding details
Available
What's required
Applicants must hold a PhD in engineering, mathematics, or a closely related discipline. Strong skills in numerical data analysis, statistical analysis, image processing, and machine learning are considered assets. Experience with X-ray computed tomography instrument error modeling and correction is advantageous. Candidates should have scientific curiosity, strong problem-solving skills, the ability to design and implement experiments, and proficiency in English communication. Teamwork, flexibility, time management, and willingness to engage in teaching, workshops, and travel are also required. Applicants must provide an academic CV, PhD, Master, and Bachelor certificates and transcripts, a motivation statement, and two academic references.
How to apply
Apply online via the KU Leuven application portal by April 30, 2026. Submit an academic CV, degree certificates and transcripts, a motivation statement, and two academic references. Early application is encouraged as the position may be filled before the deadline. For questions, contact Prof. Wenjuan Sun at [email protected].
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