PhD Position Control Theory for Self-Designing Digital Twins of Transportation Systems

The PhD Position Control Theory for Self-Designing Digital Twins of Transportation Systems builds digital twins that design themselves, using formal control theory to configure and verify them, then puts that theory to work on transportation systems.

Job description

On this PhD project you will delve into the growing field of digital twins for infrastructure systems, with a focus on transportation systems. Digital twins are high-fidelity simulations combining principle-based models and black-box/data-driven representations of physical systems. While essential for high-accuracy predictions and counterfactual analysis, they are inherently complex and difficult to analyze due to the lack of standardization and a unified design theory.

This project will tackle this problem from a theoretical angle in three main ways:

• You will develop a framework for the autonomous design of formal mathematical contracts, based on the system description and functional requirements. This will lead to the creation of abstract classes used to describe the digital twin.
• You will then design methods for automatically choosing the right parametrization of controllers to autonomously configure them to the abstract classes, ensuring stability and performance based on the requirements and specifications, e.g. via federated, scenario/sampling-based contract compositions.
• Additionally, you will theorize how to design and verify complex control policies such as MPC and RL.
• Additionally, you will study the effect of interconnecting digital twins of different systems and the effect on their stability.

You will be able to work towards improving our state-of-the-art advanced digital-twin of transportation systems (based on SUMO).

You will work at the Delft Centre of Systems and Control (DCSC) and will be supervised by Carlo Cenedese & Manuel Mazo.

TU Delft is a top tier university and is exceedingly active in the field of Artificial intelligence and Control Systems. The Delft Centre for Systems and Control (DCSC) coordinates the education and research activities in systems and control at Delft University of Technology. The Centre's research mission is to conduct fundamental research in systems dynamics and control, involving dynamic modelling, advanced control theory, optimisation and signal analysis. The research is motivated by advanced technology development in physical imaging systems, robotics and transportation systems. The group actively participates in the Dutch Institute of Systems and Control (DISC).

Job requirements

• An MSc degree in systems and control, applied mathematics, electrical engineering, computer science, or related fields.
• Basic knowledge of control theory and/or machine learning and/or digitl twin technologies (waived if the candidate is particularly skilled on theoretical computer science, optimization, or mobility systems).
• Strong analytical skills and an ability to work at the intersection of several research domains, in particular control theory, computer science, and transportation engineering.
• Good programming skills are expected, in particular Python. Knowledge of other programming lenguages is not mandatory but apprecated.
• Good command of the English language and good communication skills.
• Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis.

TU Delft (Delft University of Technology)

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.

Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty Mechanical Engineering

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3204 - €4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

• FTE: 1,0

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. The assessment takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed.