Master thesis available

"Machine Learning Approaches for Quantitative Microscopy"

Machine learning (ML) methods are getting more and more importance for biomedical microscopy and can outperform conventional image processing approaches. Recently, several frameworks have been developed, which try to bridge the gap between model development and their generic use for biomedical image analysis. Although MHH recently established a state-of-the-art cluster for scientific computing, the environment for custom-tailored ML applications still has to be developed.


If you are interested in the application of advanced microscopy techniques to study molecular mechanisms of the serotonergic signalling cascade, please do not hesitate to get in contact with us.
Positions at the different levels are available.

Interested students are cordially invited to visit our department and to arrange an appointment with:

Prof. Dr. Evgeni Ponimaskin (0511 532 4858)

Dr. Andre Zeug (0511 532 5026)