Postdoc or PhD position on Robotic De- & Remanufacturing System Design

End-of-(first-)life products return with increasing volumes, a wide variety of models and conditions, and high uncertainties about which ReX strategies to adopt at the product, sub-assembly, and component levels. Prior research in the group has focused on AI-supported product model identification, pose estimation, condition evaluation, and state-of-health prediction, as well as technologies for systematically building up product and process knowledge and for structuring this information in Digital Product Passports (DPPs). This is to later leverage the acquired knowledge from these DPPs in human-robot cooperative re- and demanufacturing processes. As research activities scale and complexity increase in integrating these distinct technologies in a multi-robot, multi-operator environment, the question arises of how to improve overall system design and communication between process building blocks.

Therefore, the research group is seeking a new colleague to support the design of an enhanced framework that integrates high-level task sequencing with low-level sensor-fusion control to facilitate in-process adaptation based on human and/or robot feedback. The focus is on improving the robustness of both contact-free motions and contact-rich interactions, where uncertainties in geometry, friction, and compliance require continuous corrections during execution, and where learnings from prior actions performed on the same product or component are also leveraged.

With the ambition to boost process adaptability, while assuring overall robustness and maintainability, the target is to explore the use of physics-based simulation tools, such as Drake. The main benefits considered are the ability to model contact dynamics, validate and refine disassembly skills, and assess the physical feasibility of candidate strategies in simulation before execution, while accounting for the actual (physical) state of operations. Another benefit considered is that insights from such simulations can also support human-robot cooperative cell design to maximize task success, dexterity, and execution efficiency of various ReX activities on a variety of product models and conditions.

While main innovations are expected in control and simulation, empirical validation and demonstration are considered equally important to ensure industrial adoption. Therefore, the project will also require a hands-on approach to support the extension of the hardware in the re- and demanufacturing labs in Heverlee, validate the robustness of communication with the robots and available tooling, and support the development and dissemination of demonstrations to industry.

For both PhD and Postdoctoral candidates:

• You hold a Master of Engineering Science or Engineering Technology in the fields of Mechanical engineering, Mechatronics or Robotic Engineering, or other related field, obtained with distinction.
• You have demonstrated academic excellence and have worked on robotic/mechatronic projects either during your degree, internships, or in industrial projects.
• You have solid programming experience and are comfortable working with complex software systems.
• You write Python proficiently, and your C++ skills exceed the beginner level.
• You have experience in developing software architectures, e.g., for real-time task scheduling and execution.
• You have prior experience with PLC programming and industrial fieldbus protocols, e.g., EtherCAT adn CANopen.
• You have a creative mindset and aren’t afraid to take the initiative to look for innovative ideas and new opportunities.
• You communicate effectively in English (oral and written); Dutch is an advantage, but not required

Additional expectations for Postdoctoral candidates:

• You hold a PhD in Engineering with a high relevance to the project activities.
• You bring significant prior and relevant experience, e.g., in system design, software architecture design, real-time task scheduling, and/or robotic de- and remanufacturing.

• A position in a leading research group with a strong international track record in applied research deploying AI in reuse, repair, remanufacturing, and lifecycle engineering.
• Collaboration with companies across multiple product sectors and active in different product lifecycle stages.
• A research trajectory that blends scientific publication with real-world impact, supporting both academic excellence and industrial relevance.
• Competitive salary and employment conditions according to KU Leuven standards.
• An attractive multi-disciplinary and multi-cultural working environment, and up to 1 day per week home office.
• For PhD researchers: the opportunity to complete a PhD in a highly relevant industrial–academic environment.

• For Postdoctoral researchers: the opportunity to grow into a technical leader in a strategic field of research within the Flemish and European research ecosystem.