PhD candidate in Digital Twin Frameworks for sustainable manufacturing of multi-material products

A PhD position is available in the Advanced Production Engineering (APE) research group at the Engineering and Technology institute Groningen (ENTEG), Faculty of Science and Engineering.

In the application of materials, there are distinct worlds plastic and metal. Metal is strong, conductive and wear resistant. On the other hand is plastic is able to create complex shapes. The combination is challenging from the perspective of recyclability, adhesion and expansion coefficient, which creates stresses.

We are seeking a motivated PhD Researcher to work on new methods for applying circular and multi-material systems in modern manufacturing. The work focuses on plastics and metals for hybrid design and analysis studies. The project develops an integrated digital framework in the context of multi-materials in which materials research and physical testing form the validated foundation, enabling Digital Twins and AI-based decision support for design and process choices. This full-time position offers access to advanced laboratories, simulation environments, and a multidisciplinary research setting.

For this position, we are looking for someone who has:

• Master’s degree in Materials Science and Engineering, Production Engineering, or a related field.
• Strong background in materials, simulation, AI/ML, or manufacturing processes.
• Experience with plastics and metals.
• Independent, creative, and collaborative working style.
• Strong communication skills in English (oral and written).
• English proficiency: IELTS = 6.5 (academic) or TOEFL computer-based = 237 or TOEFL internet-based = 92.

As a PhD student, you will contribute to the development and validation of an integrated approach for multi-material and multi-step simulations using advanced digital engineering tools. Your work will span circular materials research (plastics and metals), the creation of high-quality material models, the development of Digital Twins, and the use of AI-based methods. This includes building model-ready databases, developing simulation chains that link process simulations with analysis, making workflows for validation, and contributing to developing AI-driven tools that integrate performance evaluations, processing windows, and circularity-related data.

For more information about the APE group please use the following link: www.rug.nl/research/ape

Questions about your application process?

You may contact Friso Salverda, Human Resources Adviser, f.d.salverda@rug.nl