Vacancy: Ph.D. Position

If first html tag is indented, and this include is called after a list, the html tag is considered a list element, and things go wrong. Leaving a hidden unindented line here

If first html tag is indented, and this include is called after a list, the html tag is considered a list element, and things go wrong. Leaving a hidden unindented line here

Topic: Vision-Driven Robot Manipulation with Foundation Models


  • Position: Ph.D. Student
  • Location: KU Leuven, Leuven, Belgium
  • Starting Date: Fall 2024
  • Duration: 4Y
  • Supervisor: Renaud Detry
  • Announcement Posted On: June 11, 2024
  • Status: open


KU Leuven is seeking a highly motivated PhD student to work on robot learning for vision-driven manipulation. The project focuses on using multi-modal foundation models to facilitate the acquisition of manipulation skills. Initially, the agent will passively observe tasks commanded via tele-operation, then gradually learn to mimic the behavior of the operator, eventually achieving autonomous operation. Specific objectives will be established jointly with the successful candidate.


KU Leuven is Belgium’s largest university and a leading higher education and research institution, ranked among the top 100 universities worldwide. The offer includes:

  • A four-year fully funded PhD position at one of Europe’s top universities,
  • A competitive salary or tax-free scholarship,
  • State-provided health insurance,
  • A thorough scientific education within a specialized doctoral training program,
  • The opportunity to participate in international conferences and workshops,
  • Working with two thriving research teams: group PSI (Electrical Engineering) and group RAM (Mechanical Engineering),
  • Working in Leuven, a charming city located a short 20-min train ride from Brussels.


  • Carry out research on the project specified above and publish findings in top-tier robotics, computer-vision and machine-learning journals and conferences,
  • Assist in the supervision of Master’s thesis students,
  • Perform a limited amount of teaching activities (on average three hours per week).


The successful candidate must:

  • Hold a degree(s) in engineering, physics, math, computer science, or a related field, with a strong background in machine learning and/or computer vision, acquired either through coursework or self-study,
  • Demonstrate research experience (e.g., through Master’s thesis or research internship),
  • Demonstrate the ability to assist with TA work, either with a degree in EE or ME, or with transcripts of courses relevant to EE or ME.

Proof of English proficiency is required before admission: SET Language Requirements. Applicants who already have proof are welcome to include the relevant documents in their application.


Applicants must submit the following files:

  • A cover letter (, produced by filling this form (submitted as Markdown, not PDF),
  • A curriculum vitae (cv.pdf). There will be redundancy between the CV and the cover letter, that’s ok. In your CV, please highlight in yellow at most 3 items that you feel make you stand out, such as:
    • a scientific paper you have published,
    • recognition of excellence in your educational program (e.g., top X% of your class),
    • the competitive nature of your educational program, or a ranking of your university (nationally or worldwide),
    • performance/grades in key courses,
    • or any other achievement that makes your profile particularly relevant for the role.
  • A copy of academic transcripts (Bachelor’s/Master’s grades) (bachelors-transcripts.pdf, masters-transcripts.pdf),
  • Proof of English proficiency (if available) (language-cert.pdf), see SET Language Requirements.

Do not bundle these files in a compressed archive (no .zip, no .rar). Instead, process each PDF with Ghostscript using the following command:

gs -q -dNOPAUSE -dBATCH -dSAFER -sDEVICE=pdfwrite -dPDFSETTINGS=/ebook -sOutputFile=output.pdf input.pdf

Applications should be submitted by email to Questions can be directed to the same address.

Please note that this vacancy is also announced on KU Leuven’s Jobsite. Do not apply via the university’s jobsite, i.e., do not click on the blue “Apply for this position” button nor the “online application tool” link of this page. Instead, submit your application by email as instructed above.

Applications can be sent immediately and will be evaluated until the position is filled.

Applications submitted before July 3, 2024, will be given preference.