Are you fascinated by cutting-edge additive manufacturing technologies and eager to develop and build experimental setups and combine this with physics-based modelling? Join us as a PhD candidate and contribute to making volumetric 3D printing predictable, reliable, and industry-ready.
InformationAdditive manufacturing enables unprecedented design freedom, but today's technologies still struggle with predictability, efficiency, and material waste. A promising new approach, Tomographic Volumetric Additive Manufacturing (TVAM), can fabricate complex 3D objects in a single step without support structures. However, industrial adoption is currently limited by the lack of predictive process and material models.
As a PhD candidate, you will work on the M2i-funded research project "Multiphysics Modelling of Tomographic Volumetric Additive Manufacturing Processes for Predictive Product Properties (MTV)". Your research focuses on the experimental and material-modelling foundations required to enable predictive and controlled TVAM.
You will be embedded in the Processing & Performance section of the Department of Mechanical Engineering at Eindhoven University of Technology and closely collaborate with a second PhD candidate focusing on process-scale modelling. The project is carried out together with the industrial partner Motion Imager and international academic collaborators.
Your main responsibilities include:
- Designing and building an experimental TVAM setup for simple and complex geometries.
- Experimentally characterising photopolymer curing behaviour, including reaction kinetics, shrinkage, thermal effects, and mechanical property evolution.
- Developing physics-based constitutive material models describing liquid-to-solid transitions and viscoelastic behaviour under light exposure.
- Validating material models using experimental data and applying them to complex printed geometries.
- Contributing to integrated demonstrations of predictive TVAM processes together with modelling and industrial partners.
- Publishing your results in leading scientific journals and presenting them at international conferences.
- Supervising MSc and BSc students and contributing to teaching activities.
Through your work, you will directly contribute to reducing material waste, enabling "first-time-right" manufacturing, and advancing digital twins for next-generation additive manufacturing.