With my background in biophysics, medicine and computation, my projects cover a wide range of expertise. I like to bring different disciplines into contact. This pages provides an overview.


Before my medical degree, I studied the field of biophysics at Delft University of Technology, where I worked in several labs. At the Swiss Federal Institute of Technology, I familiarised myself with machine learning and computation. On the side, I have also been a dedicated teacher in programming and electronics. During my medical school (Utrecht University), I worked on bioartificial organs in the Nephrology group. Medicine has been my passion ever since.


Biophysics
Medicine
Computation


Genome-wide off-target cleavage prediction using statistical physics

CRISPR/Cas nucleases


Organoid-based kidney-on-a-chip transplanted on chorioallantois

Transplantable kidney


Liquid-liquid phase separation for bedside nucleic acid detection

Coalescence-based diagnostics


Teaching material for a TU Delft course about electronics and data acquisition

Electronic instrumentation


Generally, it thrives me most to find a technical edge in biomedical projects. During my work on CRISPR/Cas nucleases, for instance, I combined wet lab experience with mathematical modelling. This lead to a situation where theoretical insights can vouch for phenomena in practice and vice versa.


Transferable skills:

  • Analytical reasoning, problem solving, critical thinking
  • Teamwork and leadership
  • Teaching
  • Wet lab skills
  • Computational and numerical methods
  • Programming in Python, MATLAB, R