Summary
Are you fascinated by the intersection of control theory and scientific machine learning? Join the Eindhoven University of Technology (TU/e) for a PhD project focused on developing the mathematical foundations needed to make deep operators reliable, robust, and applicable for the control of complex engineering systems. This project involves investigating how operator-learning models can represent dynamical systems, characterizing their stability and robustness, and designing controllers for them. The work combines rigorous theory, numerical methods, and applications in high-tech, medical, and energy systems.
PhD in Control Theory for Learned Operators in Dynamical Systems at Eindhoven University of Technology, Netherlands
Designation
PhD Candidate / Scientific Staff
Details
| Field of Expertise | Organisation | Full-time Equivalent | Salary Range |
|---|---|---|---|
| PhD | Department of Mechanical Engineering, Eindhoven University of Technology | 1.0 FTE | € 3,204 – € 4,051 gross base salary per month |
Research Area
- Control Theory
- Scientific Machine Learning
- Operator Learning Models
- Dynamical Systems
- System-Theoretic Properties (Stability, Contraction, Dissipativity, Robustness)
- Optimization
- Applied Mathematics
Location
Eindhoven University of Technology, Eindhoven, Netherlands
Eligibility/Qualification
- A master’s degree (or an equivalent university degree) in Systems and Control, Mechanical Engineering, Electrical Engineering, Applied Mathematics, or a closely related field.
- A research-oriented attitude and strong curiosity for fundamental research.
- Experience with and a strong interest in machine learning and artificial intelligence, and enthusiasm for combining these methods with systems and control theory.
- Excellent analytical and mathematical skills, with an interest in developing new theoretical results.
- An enthusiasm for combining theoretical research with numerical implementation.
- Ability to work independently while contributing effectively to an interdisciplinary research team and with industrial partners.
- Motivated to develop teaching skills and coach students.
- Fluent in spoken and written English (C1 level).
Scholarship Description
This PhD project offers a unique opportunity to contribute to cutting-edge research at the intersection of systems and control theory, scientific machine learning, operator theory, optimization, and applied mathematics. As a PhD candidate, you will develop a new systems and control theory for learned operators, bridging modern scientific machine learning with classical control theory. Your research will address fundamental questions regarding state-space representation, stability, robustness, and controller design for systems represented by learned operators. You will be part of the Dynamics and Control group at the Department of Mechanical Engineering, supervised by dr.ir. Fahim Shakib and prof.dr.ir. Nathan van de Wouw, and will work in an interdisciplinary environment with opportunities for academic and industrial collaboration.
Conditions of Employment:
- Full-time employment for four years, with an intermediate assessment after nine months.
- Minimum 10% and maximum 15% of annual employment dedicated to teaching tasks.
- Salary and benefits in accordance with the Collective Labour Agreement for Dutch Universities, scale P (€ 3,204 – € 4,051 gross base salary per month, full-time).
- 8% holiday allowance and 8.3% year-end bonus.
- Generous leave options: 29 standard days per year, extendable to 41 days.
- Participation in the ABP pension scheme (TU/e pays 70% of premium).
- High-quality training programs and support for scientific researchers.
- Excellent technical infrastructure and on-campus children’s day care.
- Unlimited access to the TU/e Student Sports Center at an affordable rate.
- Wellbeing support via OpenUp (mental health services).
- Allowance for commuting, working from home, and internet costs.
- Staff Immigration Team and tax compensation scheme (Expat Scheme) for international candidates.
How to Apply
Interested candidates are invited to submit a complete application online using the apply button on the official vacancy page. Applications sent via email or post will not be processed. The application should include:
- A cover letter describing your motivation and qualifications for the position.
- A Curriculum Vitae (CV), including a list of your publications and the contact information of three references. (Please note that references may be contacted at any stage of the recruitment process; it is advisable to notify your references upon submitting your application).
Priority will be given to complete applications. A pre-employment screening (e.g., knowledge security check) may be part of the selection procedure.
Last Date for Apply
October 18, 2026
Apply Link
