Are you passionate about the modelling of complex dynamical systems using both physics-based knowledge and machine learning? Are you interested in synergizing these techniques to construct models with superior predictive capacity? Are you eager to apply and valorize scientific results in this field in high-tech domains such as semiconductor machines, together with a highly innovative company? Would you like to work in a team of 2 PhD students? Then, this PhD position is made for you!
InformationWe invite highly motivated students with a strong background in dynamical systems, machine learning, and mathematical system theory to apply this PhD position within the Dynamics and Control section at the Department of Mechanical Engineering, Eindhoven University of Technology. The mission of the
Dynamics and Control Section is to perform research and train next-generation students on the topic of understanding and predicting the dynamics of complex engineering systems in order to develop advanced control, estimation, planning, and learning strategies which are at the core of the intelligent autonomous systems of the future:
Designing and realizing smart autonomous systems for industry and society.The design and operation of complex high-tech systems, such as semiconductor equipment requires the construction of highly accurate (multi-physics) models to predict their behaviour. While physics-based models are still used in practice, they lack the extreme accuracy required due to unavoidable model mismatch (especially in a multi-physics context). In contrast, AI and machine learning can potentially help to construct highly accurate models; however, such models typically lack interpretability, and generalizability beyond the training dataset. This project aims to synergize both approaches in a hybrid modelling framework. As a core industrial use case, we will consider the semiconductor equipment for heterogeneous integration (hybrid bonding) of ASMPT (
https://www.asmpt.com/).
Within this project, in which 2 PhD students will be employed at the Eindhoven University of Technology, you will develop novel tools for such hybrid modeling to generate highly predictive dynamical models. This will help to design and operate the semiconductor equipment of the future. This position will help you to build both a strong academic and industrial research profile.
You will have access to the graduate courses at the Dutch Institute of Systems and Control (DISC) and the Engineering Mechanics Research School (EM), and will have the opportunity to collaborate with industry in the Brainport region and academic researchers worldwide. By joining us, you will be part of a vibrant community of more than 60 researchers including faculty members, postdocs and PhDs working on diverse topics in the field of dynamical systems and control and its applications.
This PhD position is jointly supervised by Nathan van de Wouw.