The M-Group at KU Leuven Bruges Campus invites applications for a fully funded PhD position focused on AI-assisted CAD-to-CAM optimization for machining processes. This interdisciplinary research group brings together expertise from Computer Science, Electrical Engineering, and Mechanical Engineering, with a strong emphasis on intelligent and dependable mechatronic systems. The successful candidate will join the Declarative Languages and Artificial Intelligence (DTAI) lab, renowned for its excellence in both fundamental and applied research in machine learning and artificial intelligence.

This PhD project aims to automate the CAD-to-CAM process in machining by leveraging reinforcement learning with human feedback and multi-objective optimization. The research will focus on generating and improving work plans for machining processes such as turning, milling, and drilling, using data from CAD files, historical work plans, and machining quality data. The project is part of the Flanders Make Strategic Basic Research project AutoCAM, offering close collaboration with leading industry partners and opportunities for experimental validation in state-of-the-art lab facilities.

The position offers a fully funded 4-year PhD scholarship, with a competitive remuneration package, health insurance, and access to university benefits. Doctoral training is provided through the KU Leuven Arenberg Doctoral School, and candidates will have opportunities to present their research at international conferences and collaborate within a dynamic, international research environment. KU Leuven is one of the world's top 100 universities, offering a vibrant academic setting in the historic city of Bruges.

Applicants should hold a Master's degree in Computer Science, Artificial Intelligence, Electrical Engineering, Mechanical Engineering, or a related field, with above-average academic performance. Proficiency in English and experience with machine/deep learning are required; prior experience with reinforcement learning, multi-objective optimization, and/or CAD/CAM is a plus. Candidates should be proficient in Python and familiar with data science and machine learning toolkits. The application requires a motivation letter, CV, transcripts, proof of English proficiency, and a reference letter or contact details for a referee.

KU Leuven values diversity and strives for an inclusive, respectful, and socially safe environment. The university encourages candidates from diverse backgrounds to apply. For more information, contact Prof. Mathias Verbeke at [email protected], mentioning [AutoCAM vacancy] in the subject line.