Postdoctoral Position in Computational Biology and Biomolecular Modeling & Design (W/M)

The Ecole polytechnique fédérale de Lausanne (EPFL) is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs 6,000 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of 16,000 people, including over 10,000 students and 3,500 researchers from 120 different countries.

The Laboratory of Protein and Cell Engineering at the Institute of Bioengineering of the Ecole Polytechnique Federale de Lausanne (http://bioengineering.epfl.ch/welcome) is looking for a talented and motivated post-doctoral fellow with a strong expertise in computational biology, biophysics or computational chemistry and good computer programming skills.

We belong to the Institute of Bioengineering at EPFL and are also part of the Ludwig Institute for Cancer Research (LICR) in Lausanne. While EPFL provides a world-class environment for basic science and engineering, the LICR fosters translational applications of basic discoveries to cancer medicine at the highest level. Our laboratory benefits from this dual exciting environment and interdisciplinary approaches are essential to our research. We work at the interface of computational biology, biophysics, chemistry, and cell biology to uncover the molecular principles that regulate protein and cellular signaling. Using this understanding, we (1) model and design novel protein biosensors and protein signaling networks for synthetic biology and engineered cell therapeutic applications; (2) predict the effects of genetic variations on protein structure/function and protein signaling networks for personalized cancer medicine applications. We are part of the Rosetta Commons, a community of developers of the software Rosetta (https://www.rosettacommons.org), the premier suite for macromolecular modeling, and are actively developing novel computational approaches.