Summary
Eindhoven University of Technology (TU/e) is offering a fully funded 4-year PhD position within the Control Systems Technology group, Department of Mechanical Engineering. This position focuses on pioneering research at the intersection of machine learning and control theory, developing scalable methods for expressive, flexible neural controllers with verifiable safety and stability guarantees.
PhD Position in Safe AI-Based Control at Eindhoven University of Technology, (TU/e) Netherlands
Designation
- Position Title: PhD Candidate (Promovendus)
- Personnel Type: Academic Staff (Wetenschappelijk personeel)
Key Information Overview
| Detail | Information |
| Position | PhD Candidate in Safe AI-based Control |
| Institution | Eindhoven University of Technology (TU/e) |
| Department | Department of Mechanical Engineering (Control Systems Technology Group) |
| Location | Brainport Eindhoven, Netherlands |
| Employment Type | Full-Time (1.0 FTE, 4-year contract) |
| Gross Monthly Salary | €3,204 – €4,051 gross per month (Scale P) |
| Additional Benefits | 8% Holiday Allowance, 8.3% Year-End Bonus, ABP Pension Scheme |
| Application Deadline | August 30, 2026 |
Research Area
- Domain: Control Theory, Machine Learning, & Systems Engineering, Chemistry & Materials Science
- Focus Topics:
- Safety- and verification-by-design approaches for neural-network-based controllers.
- Certifying closed-loop safety and stability using Control Barrier/Lyapunov Functions, quadratic constraints, and semidefinite programming.
- Neural-network architectures with intrinsic stability and robustness properties.
- Integration of physical insight, prior system knowledge, and baseline controllers with learning algorithms.
- Applications in robotics, high-tech motion control, and energy systems.
Location
- Campus: Eindhoven University of Technology (TU/e), Eindhoven, Netherlands (located in the Brainport tech region).
Eligibility & Qualifications
- Educational Background: A Master’s degree (or equivalent university degree) in:
- Systems and Control / Control Engineering
- Engineering Cybernetics / Mechatronics
- Mechanical Engineering / Electrical Engineering
- Computer Science / Artificial Intelligence, or a closely related field.
- Key Skills & Attributes:
- Strong interest in control theory, machine learning, and safety-critical systems.
- Mathematically rigorous and research-oriented mindset.
- Capability to work independently as well as in interdisciplinary teams.
- Motivation to coach students and develop academic teaching skills.
- Language Requirement: Proficiency in spoken and written English (C1 level).
Job Description
As a PhD candidate in this project, you will:
- Develop theoretical foundations and scalable computational methods for verifying closed-loop safety and stability in complex dynamical systems.
- Embed certifiable safety properties directly into neural controller architectures and training loops.
- Test and evaluate new control methods on benchmark problems and real-world high-tech application scenarios.
- Collaborate closely with researchers across departments and industrial partners in the Brainport region.
- Present your research findings at international conferences and publish in premier journals.
- Dedicate 10% to 15% of your employment time to teaching support and student supervision.
How to Apply
Applications must be submitted online through the TU/e Job Portal.
Required Documents:
- Cover Letter: Explaining your motivation and qualifications for the position.
- Curriculum Vitae (CV): Including a publication list and contact details for three references.
Note: Applications submitted via email or postal mail will not be processed.
Last Date to Apply
- Application Deadline: August 30, 2026
