For our Applied Research Department in the Leiden head office, we are looking for a:

Researcher (Machine Learning /Deep Learning)

The Researcher will work on the research and development of novel and existing algorithms and applications, in particular within the cardiovascular domain.


What will your role be?

In the role of Researcher you will:

  • Keep up with literature on the field of medical imaging, in particular using Deep L
  • Attend conferences and workshops in the field.
  • Come up with innovative, robust and practical solutions that will work in daily clinical routine.
  • Develop these algorithms and/or applications in Python or C++
  • Collaborate with clinical partners on the external testing, validation and feedback on our innovations.
  • Collaborate with software engineering teams to transfer these innovations from research to final product releases.


The profile we are looking for:

  • PhD / Master’s degree in computer science, engineering or imaging
  • Strong background in machine learning and deep learning
  • Experience with image processing
  • Extensive experience in programming and ability to write clean and maintainable production-level code
  • Experience with deep learning frameworks (TensorFlow and/or PyTorch)
  • Experience with medical and in particular cardiovascular applications is an asset
  • Knowledge of SciPy tools, ITK, VTK, Qt, and 3D visualization or DICOM is an asset
  • Excellent communication skills, both written and verbal, in English


Personal Skills and competences:

  • Enthusiastic team player
  • Innovator and interested in biomedical technology


What Medis offers you:

  • An attractive compensation plan
  • International, young and diverse colleagues
  • Personal growth and development plan
  • Innovative products that make a difference
  • A stimulating work environment with highly educated professionals, working on innovative products
  • A position in a field with significant growth potential and high societal relevance
  • A market-conform salary including attractive secondary conditions

If you have any questions, please contact Johan HC Reiber, PhD, CSO at / Phone secretariat: +31 (0)71 522 32 44.



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