DESCRIPTION: Delft University of Technology (TU Delft) is looking for an enthusiastic and self-motivated person with a passion for research. They offer a stimulating scientific research environment and the embedding in a multi-disciplinary consortium that allows you to develop skills that go beyond discipline-specific boundaries. You will be supervised by Jesse Krijthe (computer science, TU Delft) and Nan van Geloven (biostatistics, Leiden University Medical Center) and be primarily based in the Pattern Recognition and Bioinformatics group of TU Delft, which includes researchers working on the methodology of machine learning, bioinformatics, computer vision, and socially perceptive computing.
REQUIREMENTS:
- A critical thinker with an open mind.
- Strong interest in understanding and developing statistical and machine learning methods.
- Master’s degree in a relevant quantitative field (such as statistics, computer science, mathematics, econometrics, psychometrics, physics, etc.).
- Ability to program in Python, R, Julia or a similar (scientific) programming language.
- Proficient in spoken and written English.
CONDITIONS:
- 4-year period of employment.
- Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 - €3881 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
- PhD candidate you will be enrolled in the TU Delft Graduate School, that provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor.
- Job Location: Mekelweg 5, 2628CD, Delft (The Netherlands)
APPLICATIONS INSTRUCTIONS:
- A curriculum vitae.
- Cover letter (max 2 pages) covering your motivation, research interests and how they connect to the position.
- Transcripts
Application Deadline: 20 May 2026 Additional information: If you would like more information about this vacancy or the selection procedure, please contact dr. Jesse Krijthe, assistant professor, via This email address is being protected from spambots. You need JavaScript enabled to view it.