PhD in End-to-End AI for Mobile Autonomous Robotics

Introduction

Apply for this PhD position to research the next generation of mobile autonomous robotics. You will work on cutting-edge AI technologies for robotics, including end-to-end transformer models that enable robots to autonomously navigate and interact with open-world environments. As this PhD is part of the NWO Perspectief FIND project, you will collaborate with leading research organisations and companies, TNO and NXP.

Job Description

This PhD position concentrates on designing innovative AI architectures and training techniques for end-to-end robotics. Specifically, you will investigate Vision Language Models (VLMs), Multi-modal Large Language Models (MLLMs), and Vision Language Action models (VLAs) for applications involving spatial scene understanding and spatial reasoning. The challenge is achieving a level of spatial understanding that allows robots to handle new environments and tasks with minimal human-provided demonstrations or descriptions, while maintaining a certain level of reliable and safe operation. Another challenge particular to robotics is that these end-to-end models must be efficient enough to operate in real time. Certain tasks, e.g., collision prevention in manipulation, require guaranteed timely responses, while others, e.g., reasoning, are allowed to take longer. These ‘fast’ and ‘slow’ tasks need to be supported simultaneously by the end-to-end architecture and should be compatible with the limited compute and energy resources of embedded systems.

Your daily activities will include reviewing the latest developments in the field, identifying current limitations, hypothesising possible causes and solutions, designing improved network architectures and training methods, setting up validation methods to test hypotheses, and reporting on findings via presentations and publications. It is expected that you perform these tasks as a professional with great independence, and that you possess the ability to engage in in-depth discussions, make informed choices, and be open about the limitations of your research. Additionally, given the rapid pace of AI progress, we find it very important that PhDs not only work individually but also be eager to work in teams with students, peers, and supervisors.

Research group and company

This position is embedded in the Mobile Perception Systems (MPS) laboratory of the Signal Processing Systems (SPS) group within the Electrical Engineering department at Eindhoven University of Technology (TU/e). The MPS lab has a strong track record in researching AI architectures, specifically for vision modalities, that achieve state-of-the-art accuracy while being orders of magnitude more efficient than earlier methods. The MPS lab regularly publishes in top-tier venues such as CVPR, ICCV, and IEEE RAL. This PhD position will be supervised by Gijs Dubbelman, associate professor and head of the MPS Lab, Daan de Geus, assistant professor in the MPS Lab, and expert researchers from TNO and NXP.

This PhD project is executed in close collaboration with TNO and NXP and is part of the FIND program. FIND is a research program funded by the Dutch government and industry that brings together 5 universities, 11 companies (startups to multinationals), and 2 knowledge institutes to develop foundation models (large AI models) for the Dutch high‑tech industry, with strong emphasis on edge deployment, privacy, and timely decision‑making. Partners include ASML, NXP, Canon, ASMPT, Technolution, Signify, Shell, TNO, and others. A total of 12 PhDs will be employed on the FIND program, covering topics from foundation model pre-training and multimodal adaptation to architectures and compression for edge deployment, while targeting real-world validation in domains such as HealthTech, smart industry, and autonomous mobility.

Job Requirements

• A master’s degree in Computer Science, Artificial Intelligence, Robotics or in a strongly related field.
• The completion of a MSc thesis of high quality, potentially publishable (already published is a big plus) at top-tier venues in robotics (ICRA,CORL,IROS,RSS,RAL), computer vision (CVPR,ICCV,ECCV,WACV), or in AI (NeurIPS,ICLR,ICML,AAAI).
• Knowledge of latest generation AI architectures, including transformers.
• Strong background in machine learning theory and practice.
• Experience with deep learning framework PyTorch or similar.
• Ability to work in an interdisciplinary team.
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level or higher). 
  
  

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. € 3,059 - max. € 3,881).  
• 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. 

About us

Eindhoven University of Technology is a leading international university within the Brainport region where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community.

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.

Information

Visit our website for more information about the application process or the conditions of employment. You can also contact Floor de Groot, HR advisor, f.r.d.groot@tue.nl or +31 40 247 3040.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

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. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application.

Ensure that you submit all the requested application documents. We give priority to complete applications.

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.

Please note

• You can apply online. We will not process applications sent by email and/or post. 
• A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines.
• Please do not contact us for unsolicited services.