KU Leuven, one of Europe's most prestigious universities, invites applications for a fully funded PhD position focused on visual defect detection and identification in continuous production processes with minimal human feedback. The successful candidate will join the M-Group at KU Leuven Bruges Campus, an interdisciplinary research team specializing in intelligent and dependable mechatronic systems. The group integrates expertise from Computer Science, Electrical Engineering, and Mechanical Engineering, with a strong emphasis on applying Artificial Intelligence and Machine Learning in industrial contexts.

This PhD project aims to develop autonomous, self-learning camera-based systems for quality control in continuous production lines, such as those handling polymer products, textiles, or food. The research addresses the challenge of detecting and identifying rare and subtle defects in highly variable products, where traditional manual dataset labeling and model training are inefficient and often result in poor performance due to data imbalance. The project will focus on creating an inline system capable of learning to detect and classify defects on the fly, leveraging continuous data streams and requiring minimal human intervention for feedback and identification.

The successful candidate will be embedded within the Declarative Languages and Artificial Intelligence (DTAI) lab, renowned for its excellence in both fundamental and applied research on machine learning and artificial intelligence. Doctoral training will be provided through the Leuven Arenberg Doctoral School, which offers comprehensive support for both academic and professional development. The PhD is supervised by Prof. Mathias Verbeke and Dr. Matthias De Ryck, and is part of the Flanders Make IRVA project RETINA, which aims to enable low-effort visual defect detection and identification in industrial production processes. The research will be conducted in close collaboration with leading industry partners, providing opportunities for real-world validation and industrial impact.

Applicants should have a Master's degree in Computer Science, Artificial Intelligence, Electrical Engineering, Mechanical Engineering, or a related field, with above-average academic performance. Required skills include proficiency in English, experience with machine/deep learning, strong affinity for computer vision, and programming expertise in Python. Familiarity with data science and machine/deep learning toolkits is essential, and experience with model deployment and MLOps tools (such as Dockerization and CI/CD pipelines) is advantageous. The ideal candidate will be proactive, creative, and able to work both independently and collaboratively within a dynamic research team.

KU Leuven offers a fully funded 4-year PhD scholarship, a competitive remuneration package, health insurance, and access to state-of-the-art infrastructure and university benefits. The Bruges Campus provides a vibrant academic setting with newly established labs and close proximity to industry partners. PhD candidates are encouraged to present their research at international conferences and national events, with a strong emphasis on publishing high-quality papers and engaging with the broader research and industrial community.

To apply, candidates should use the online application tool and submit a single PDF containing a motivation letter, academic CV, list of publications (if any), copies of diplomas, transcripts, English summary of their master thesis, proof of English proficiency, and a reference letter or contact details for a referee. KU Leuven is committed to diversity, inclusion, and equal opportunity, welcoming candidates from all backgrounds.

For further information, contact Prof. Mathias Verbeke ([email protected]) or Dr. Matthias De Ryck ([email protected]). The application deadline is February 5, 2026.