PhD on Collective Decision-Making Algorithms for Autonomous Driving

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.

The mission of the Department of Electrical Engineering is to acquire, share and transfer knowledge and understanding in the whole field of Electrical Engineering through education, research and valorization. We work towards a ‘Smart Sustainable Society’, a ‘Connected World’, and a healthy humanity (‘Care & Cure’). Activities share an application-oriented character, a high degree of complexity and a large synergy between multiple facets of the field.

Research is carried out into the applications of electromagnetic phenomena in all forms of energy conversion, telecommunication and electrical signal processing. Existing and new electrical components and systems are analyzed, designed and built. The Electrical Engineering department takes its inspiration from contacts with high-tech industry in the direct surrounding region and beyond.

The department is innovative and has international ambitions and partnerships. The result is a challenging and inspiring setting in which socially relevant issues are addressed.

Introduction

Are you passionate about developing AI-driven algorithms that ensure safe, ethical, and efficient autonomous driving in complex traffic environments?

Job Description

Are you eager to tackle the scientific challenges of designing advanced collective decision-making algorithms for autonomous vehicles? In this PhD position, you will contribute to pioneering research within the AIGGREGATE project at the control systems group in the electrical engineering department. You will focus on creating model predictive control algorithms that are provably safe for autonomous driving.  Your work will involve integrating cutting-edge AI techniques with control theory to develop algorithms capable of making proactive, human-centric decisions. 

These algorithms will leverage collective and predictive state awareness to safely navigate complex scenarios involving both connected and non-connected road users. This position offers a unique opportunity to contribute to the future of mobility by addressing challenges such as minimizing unintended harm, preventing gridlocks, and enhancing user acceptance of autonomous systems. You will be part of a collaborative environment that values inclusivity and innovation, working alongside experts in control theory, autonomous systems and formal methods.

As this project spans multiple disciplines, candidates should have experience with or a strong interest in mastering critical concepts from both control engineering and computer science. The work will involve applying advanced control methods such as model predictive control and control barrier functions, alongside computer science techniques including formal specifications, rigorous testing, and formal verification.

If you are driven by the opportunity to develop intelligent, trustworthy decision-making systems that make a tangible real-world impact, we warmly invite you to apply and join our innovative research team.

Job Requirements

• A master’s degree (or an equivalent university degree) in computer science, control engineering, robotics, automotive technology, or equivalent
• Proven programming skills in python or C++, experience with ROS2 is also a plus
• Experience with dynamic programming, Model predictive control, and formal methods.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

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 assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
• 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. € 2,901 max. € 3,707).  
• 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. 

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager dr. Sofie Haesaert ([email protected]).

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services Flux ([email protected]).

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.

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.