PhD on combined physics- and machine learning-based modeling of complex dynamical systems

Introduction

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!

Job Description

We 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.

Job Requirements

• A master’s degree (or an equivalent university degree) in dynamical systems, mechanical engineering, electrical engineering, AI and machine learning or applied mathematics.
• Strong background in dynamical systems, systems theory, and machine learning.
• Affinity with application domains within mechanical engineering such as mechatronics or robotics.
• Knowledge of at least one programming language: Matlab, Python, is expected.
• Experience and/or a keen interest in the field of dynamical systems, and machine learning.
• Eager to work within a team and independently.
• Ability to collaborate with industry and academic researchers.
• Fluent in spoken and written English.

Conditions of Employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you: 

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 2,901 max. € 3,707).  
• A year-end bonus of 8.3% and annual vacation pay of 8%. 
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. 
• An excellent technical infrastructure, on-campus children's day care and sports facilities.  
• An allowance for commuting, working from home and internet costs. 
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates. 

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager prof.dr.ir. Nathan van de Wouw, N.v.d.Wouw@tue.nl, https://vandewouw.dc.tue.nl/. IMPORTANT: always put Mrs. Geertje Janssen-Dols in cc in all your communication (G.Janssen-Dols@tue.nl).

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services Gemini, HRServices.Gemini@tue.nl or HR Advice, HRAdviceME@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the 'apply now'-button on this page. The application should include the following documents as a single PDF file:

• Curriculum vitae, including a list of your publications (if applicable) and the contact information of references.
• An explanation of your interest in the proposed research topic.
• Copies of diplomas and academic transcripts with grades from prior university studies.
• Brief description of your MSc thesis and/or relevant research projects.

We look forward to your application and will screen it as soon as we have received it. Screening will continue until the positions have been filled.