How to Apply

If you want to work with us feel free to directly get in touch per mail. Please be specific and concisely explain your background and interests, and also don’t forget to mention why you are particular interested in working with us. Generic and unspecific applications that fail in explaining so will not be answered.

PhD Students / Postdocs

Please provide the following documents:

  • Cover letter indicating your background, interests and motivation
  • Complete course transcripts (Bachelor’s & Master’s)
  • Self-assessment (see below)
  • Contact information of at least two references

Bachelor’s / Master’s thesis

We are offering various research-oriented topics for student projects. Most commonly, students explain their interests and provide some information about their background (see below), and then we offer a project if there is a suitable topic available. We generally do not supervise external theses, but we are open to discussing own ideas of students for projects – before you propose a project idea, please check whether it is relevant to our research interests.

There are no formal requirements, but we encourage you to provide the following information:

  • Brief explanation of your interests
  • Course transcripts (Bachelor’s & Master’s)
  • Self-assessment (see below)


Your application should include a self-assessment in which you assign grades from 1-5 (1 means best) to indicate your background in relevant topics. In case you get selected for an interview it will be based on your self-assessment.

Since we may not be familiar with all international grading systems it is recommended that international applicants provide a short summary on the ranking of their university (e.g. ‘Top 10% in India’), and also rank their total grade (e.g. ‘Top 20% of students across all computer science graduates at the university’).

You can use the following template (feel free to leave topics with no experience blank):

linear algebra: 
analysis & calculus: 
algorithms & data structures: 
computer vision: 
computer graphics: 
geometry processing/shape analysis: 
mathematical optimisation: 
deep learning: 

ranking of my university: 
ranking of my performance: