D-BSSE Department of Biosystems Science and Engineering Image


The D-BSSE is one of the ETH Zurich's youngest departments and the only one located in Basel outside of the Zurich campus. The unique blend of researchers in this department makes it an exciting venue for academics interested in biological questions.


What kind of research do we do?

The D-BSSE includes researchers from disciplines such as Biology, Chemistry, Physics, Mathematics, Computer Science (Informatics), and Engineering. The collective aim of the department can be summarized as follows:

1. Discover new facts about the functionality of living systems

2. Take these new findings and try to model them

3. Use the resulting models to devise and engineer novel biosystems



From blue pill to blue light

Foto: iStockphoto.com

Taking men’s concerns seriously: ETH biotechnologists are developing a biotech solution for erectile dysfunction that consists of a gene construct and a blue light. Read more 


British NC3Rs award (£ 5000) to Olivier Frey and coworkers

Olivier Frey receives NC3Rs award

A highly commended Award (£ 5000) in the 3Rs Prize competition 2014 of the British National Center for the Replacement, Refinement and Reduction of Animals in Research was granted to Olivier Frey and coworkers. Read more 


How to loose weight - Prof. Fussenegger's article in SonntagsBlick

Prof. Martin Fussenegger

Prof. Fussenegger talks about the newest natural method to loose weight. Read more 


ETH Zürich appoints Prof. Jörg Stelling to Full Professor

Prof. Jörg Stelling

At its meeting of 4/5 March 2015, the ETH Board appointed Prof. Jörg Steling to Full Professor. Read more 


Coordination of Initial Training Network “Machine Learning for Personalized Medicine” moves to D-BSSE

MLPM logo

ETH Zurich is the new coordinating organization of the Marie Curie Initial Training Network on “Machine Learning for Personalized Medicine” (MLPM2012). Prof. Borgwardt from D-BSSE continues to act as the Scientific Coordinator of the network. Its goal is to train 14 highly qualified early-stage researchers in the fascinating and rapidly emerging field of Machine Learning in Personalized Medicine.  Read more 

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