Simulation-based design is a powerful tool assisting the development and maintenance of many engineering systems, for example in the high-tech, robotics or automotive domains. However, their increasing complexity in materials, components and physical requirements push classical model-based simulation techniques to their limits. Such systems are often modelled by coupling separate subsystems of dynamical equations with highly heterogeneous properties. The reasons for such a modular approach are to support component-based design, different type of model hierarchies, or to allow for a multiphysical characterization of their dynamics. The repeated simulation, e.g., for optimization of such complex interconnected systems leads to prohibitively large simulation times, which makes an automated design process unfeasible.

One way to overcome this is by creating cheaper surrogate models, that are faster to evaluate. However, this come at the cost of accuracy. Recently, great advancements have been made in the field of data-based surrogate modelling, which uses machine learning methodologies to construct these reduced models. The aim of this project is to develop a framework to construct and analyse such (data-based) surrogate models of coupled dynamical systems with kinematic constraints.

Job Description

Within this project you will work on developing a framework that enables the fast simulation of engineering systems that are (partially) modelled with a multibody systems approach. For that, you will use a data-based surrogate modelling approach and study appropriate simulation techniques for the resulting coupled,  heterogeneous dynamical systems with constraints described with differential-algebraic equations. The main challenges and workpackages are:

• The appropriate handling of the constraints at subsystem level when generating the data-based surrogate models.
• The development of an analysis framework for the propagation of subsystem errors in the coupled system model, and of new methods to mitigate those errors.
• The development of methodologies to simulate the resulting heterogeneous system appropriately ensuring stability and reducing computation time.

Embedding

You will execute this project in the Autonomous and Complex Systems group of the Dynamics and Control (D&C) section at the Department of Mechanical Engineering of the Eindhoven University of Technology.

The mission of the Dynamics and Control Section, which consists of 22 faculty members and 45 researchers, 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.

Moreover, the project will offer you an extensive training program in the scope of the Graduate School of Engineering Mechanics (https://engineeringmechanics.nl/), and, within TU/e, focusing on more generic and transferable skills required by professional researchers. This provides you with a solid background for your research and future career.

• You have experience with or a strong background in mechanical engineering, (applied) mathematics, physics and computational engineering, especially in the context of modelling and simulation. Preferably, you finished a Master's program in the areas of (Applied) Mathematics, (Applied) Physics, Mechanical Engineering, Computer Science, Systems and Control, Electrical Engineering or equivalent.
• You enjoy programming.
• You have a research-oriented attitude.
• You have good communication skills.
• You are motivated to develop your teaching skills and coach students.
• You are fluent in written and spoken English (knowledge of Dutch is not required).

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 evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• 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. €2,872 max. €3,670).
• 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.

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 

Information

Do you recognize yourself in this profile and would you like to know more?
For information about the project please contact the main supervisor: I. Cortes Garcia (i.cortes.garcia@tue.nl).

Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.Gemini@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 button.
The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.
• Transcript of BSc and MSc courses with grades.
   

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.