Data-Driven Digital Twins for Flexible Demanufacturing Systems

• You hold a Master’s degree in Science, Engineering, or an equivalent degree which you have obtained with a high GPA.
• You enjoy to work in a multidisciplinary team of international researchers and show willingness to learn and explore innovative technologies and techniques.
• You have a creative mindset, enjoy taking initiative, and engage in exploring innovative ideas and new opportunities.
• You are fluent in English.
• You are member of a multidisciplinary research group working on the topic of Digital Twins for Smart Manufacturing Systems at KU Leuven under the supervision of Prof. Giovanni Lugaresi and Prof. Jef Peeters.
• You study and critically evaluate existing literature, patents, company releases, and use the obtained information to determine the state of the art and to identify opportunities for novel contributions.
• You are actively engaged in the development of innovative methods and algorithms to be integrated in a digital twin architecture for (de) manufacturing systems.
  
• You contribute to organizing and performing testing and validation experiments within the lab setups available at the laboratories of KU Leuven.
• You disseminate your research results in the occasion of project meetings and at international conferences.
• You publish in high-quality international scientific journals.

The PhD ambition is to enable next-generation digital twins to become effective decision-support systems within re- and demanufacturing environments, reaching a higher integration with existing software components, databases, as well as control systems. In this project, different methods will be explored to further extend critical functionalities of simulation-based digital twins (discrete event simulation). Among others, research will be focused on methods for data-driven model generation (e.g., object centric process mining) and physical-to-digital alignment, focusing on the added value of Digital Product Passports and online measurements. The developed methods will be tested in experiments within both digital and realistic prototypical environments. The PhD is linked to the funded C+ project DIGITAU (2-years funding), which complements the C2 project AUDRI, focusing on the integration of process-level information of incoming products to be disassembled to update prediction models in a Digital Twin Framework. The final goal is to achieve a Digital Twin that adapts to product features and process conditions, allowing for the successful industrialization of a disassembly plant. The KU Leuven research group within the Department of Mechanical Engineering has significant experience in digital twins for manufacturing systems. The main industrial applications are discrete manufacturing processes such as assembly lines, as well as re- and demanufacturing processes. The group’s ambition is to enable next-generation digital twins to become effective decision-support systems within production environments, reaching a higher integration with existing software components, databases, as well as control systems.

• We offer a varied and challenging job in close cooperation with industry, combined with an attractive salary package.
• We offer a research position in a stimulating and multi-disciplinary environment and a strong industrial network.
• We provide the opportunity to work towards obtaining a PhD degree and/or to grow your academic experience and track record within an international network.
• Expected start date: 01/06/2026 - 01/09/2026