Delft University of Technology (TU Delft) is inviting applications for a fully funded 4-year PhD Position in Control Theory for Self-Designing Digital Twins of Transportation Systems. Hosted at the Delft Centre for Systems and Control (DCSC) within the Faculty of Mechanical Engineering, this doctoral research project bridges the gap between formal control theory, artificial intelligence, and complex mobility infrastructure.
PhD Position in Control Theory for Self-Designing Digital Twins of Transportation Systems at TU Delft
Overview Table
| Detail | Information |
|---|---|
| Designation | PhD Candidate / Doctoral Researcher |
| Host Institution | Delft University of Technology (TU Delft) |
| Faculty / Department | Faculty of Mechanical Engineering / Delft Centre for Systems and Control (DCSC) |
| Research Area | Control Theory, Digital Twins, Transportation Systems, Machine Learning |
| Location | Delft, Netherlands |
| Employment Type | Full-time (38–40 hours per week, 4-year contract) |
| Salary Range | €3,204 – €4,051 gross per month plus 8% holiday allowance and 8.3% year-end bonus |
| Application Deadline | 14 October 2026 |
Designation
PhD Researcher / Doctoral Candidate in Systems and Control Engineering.
Research Area
Formal Control Theory, Autonomous Contract Design, Optimization, Machine Learning (RL, MPC), Simulation and Modeling, and Smart Mobility / Transportation Systems.
Location
Delft, South Holland, Netherlands (Delft University of Technology, Faculty of Mechanical Engineering).
Scholarship & Position Description
Digital twins are high-fidelity simulations that integrate principle-based dynamic models with data-driven physical system representations. Although critical for accurate forecasting and counterfactual analysis, their complex architectures currently lack unified design theory and standardization.
As a PhD candidate on this project, you will develop formal control frameworks that enable digital twins to configure and verify themselves autonomously. Key research objectives include:
- Developing a mathematical framework for the autonomous design of formal contracts based on system descriptions and functional requirements.
- Designing automated controller parametrization methods that guarantee stability and performance (e.g., federated and scenario/sampling-based contract compositions).
- Formulating and verifying advanced control policies, including Model Predictive Control (MPC) and Reinforcement Learning (RL).
- Analyzing interconnected digital twins and their collective dynamic stability.
- Validating theoretical models on state-of-the-art transportation twin platforms (e.g., SUMO).
Doctoral candidates will be supervised by Dr. Carlo Cenedese and Dr. Manuel Mazo at the Delft Centre for Systems and Control (DCSC) and will be enrolled in the TU Delft Graduate School, offering dedicated training, doctoral courses, and relocation support through the Coming to Delft Service.
Eligibility / Qualification
Candidates must meet the following criteria to be considered:
- Academic Degree: An MSc degree in Systems and Control, Applied Mathematics, Electrical Engineering, Computer Science, Mechanical Engineering, or a closely related discipline.
- Domain Knowledge: Foundational knowledge in control theory, machine learning, or digital twin technologies. Strong theoretical backgrounds in optimization, computer science, or mobility systems are also welcomed.
- Technical Skills: Proven analytical capabilities and strong programming skills, particularly in Python.
- Language Proficiency: Excellent command of spoken and written English, meeting the TU Delft Graduate School admission requirements.
- Interdisciplinary Aptitude: Ability to work effectively at the intersection of control theory, computer science, and transportation systems.
How to Apply
Applications must be submitted online via the TU Delft vacancy portal. Applicants are required to prepare and upload the following PDF documents:
- Document 1: A 1-page motivation letter addressing Dr. Carlo Cenedese and a comprehensive Curriculum Vitae (CV) highlighting relevant achievements.
- Document 2: Official academic transcripts of both your Bachelor’s (BSc) and Master’s (MSc) degrees.
- Document 3: A sample of scientific writing (e.g., an MSc thesis chapter, conference paper, or research report).
Note: Applications sent by email or regular post will not be processed.
Last Date for Apply
The closing date for applications is 14 October 2026.
Apply Link
Interested candidates can view the full official announcement and apply directly via the university career portal:
Apply Online at TU Delft Careers
