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PhD on Foundation Models for Embedded and Embodied AI in Autonomous Driving

PhD on Foundation Models for Embedded and Embodied AI in Autonomous Driving

Position
PhD-student
Irène Curie Fellowship
No
Department(s)
Mathematics and Computer Science
FTE
1,0
Date off
22/12/2024
Reference number
V32.7703

Job description

We are seeking to fill a PhD position in the Data and Artificial Intelligence Cluster, within the Faculty of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). You will join a vibrant and diverse team of 15 faculty members and over 40 PhD students and postdocs who are advancing the science and engineering of data, machine learning, AI systems, and applications.

You will be part of the HORIZON Research and Innovation Actions project titled "SYNERGIES: Real and synthetic scenarios generated for the development, training, virtual testing, and validation of CCAM systems."

This project is part of a large program in collaboration with many academic and industrial partners, including major OEMs in Europe, with a significant impact on the future of safe AD deployment. You will be building foundation models for both embedded and embodied AI, focusing on LLM-guided sparsity and learning agents. Your work will involve language-based navigation, training, labeling (and data curation in general), as well as developing more intuitive LLM-based active learning approaches. Ultimately, you will work towards LLM-based scenario descriptions for actor generation in simulations.

Your research will aim to advance the state of the art in foundation models by making them more efficient, inspired by the human brain and memory-based learning and tracking approaches. This will contribute to the development of efficient scene generation and understanding, laying the foundation for safe and efficient autonomous driving deployment in Europe.

You will participate in cutting-edge research, publish your work in leading machine learning and AI conferences and journals, contribute to open-source tools, and collaborate closely to make these tools applicable in real-world autonomous driving contexts. You will have opportunities to present your work at high-profile scientific meetings and conferences. Your primary base will be in Eindhoven, where you will work under the supervision of Mykola Pechenizkiy and Bahram Zonooz.

Your main activities will include:

  • Advancing the state of the art in scenario generation and synthetic data for autonomous vehicles.
  • Creating working software prototypes.
  • Collaborating closely with use-case partners to apply your research results to real-world problems, using real data and interacting with real users.
  • Publishing and presenting papers in top conferences and journals.
  • Developing your professional network and collaborating with other PhD candidates in the DAI cluster, the Synergies consortium, and beyond.

Job requirements

  • MSc degree in Computer Science, Machine Learning, AI, or a related field.
  • A solid background in science or engineering.
  • Experienced in Python and PyTorch.
  • Excellent command of English. If English is not the candidate's native language, a high score on TOEFL or a similar test, and/or evidence of academic writing in English is required.
  • Self-motivated, enthusiastic, proactive, and goal-oriented.
  • Ability and willingness to work independently, as well as within an interdisciplinary team including domain experts.
  • The ability and willingness to facilitate and co-supervise MSc thesis projects related to the project will be considered an advantage.
  • Experience with open-source software will be considered an advantage.
  • Publications in top-tier conferences and journals (e.g., ICLR, ICML, NeurIPS, TMRL, etc.) will be considered additional advantages.

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 evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • 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 (€2,901 in the first year and €3,707 in the final year).
  • 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 and application

About us

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. 

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

Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager Dr. Bahram Zonooz, b.zonooz@tue.nl and/or prof.dr. Mykola Pechenizkiy, m.pechenizkiy@tue.nl .

Visit our website for more information about the application process or the conditions of employment.

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 explaining your motivation and qualifications for the position.
  • Detailed Curriculum Vitae, including contact details of referees.
  • Your publications, if any (or links to download).
  • A transcript of your grades.
  • Copies of your degrees and diplomas
  • A copy or a link to your Master thesis. If you have not completed it yet, please explain your current situation.

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.