piwik-script

Intern
Physics of Parasitism

Philip Kollmannsberger

Center for Computational and Theoretical Biology (CCTB)

Campus Hubland Nord 32
Universität Würzburg
97074 Würzburg
Germany
Tel: 0931 - 31 83961
email: Philip.Kollmannsberger@uni-wuerzburg.de
Website: https://go.uniwue.de/cia

Philip Kollmannsberger

...studied physics in Erlangen (1998-2004) and Joensuu/Finland and graduated with a diploma thesis on acoustic detection of high-energy neutrinos. He then moved towards biophysics and joined the lab of Ben Fabry in Erlangen, where he investigated the nonlinear mechanical properties of living cells using magnetic microrheology. After two short research visits to the Scripps Institute in La Jolla/USA (2006/2007) and receiving his PhD in 2009, the next step was a two-year postdoc at the Max Planck Institute of Colloids and Interfaces in Golm (2010/2011), where he studied bone cell networks and biomaterials. With a Marie Curie fellowship, he moved to ETH Zurich to work on microtissue mechanobiology (2012-2016) before starting his own research group as a Junior Professor of Computational Image Analysis at the CCTB, University of Würzburg in 2016.

- since 2016: Junior Professor (W1) and Group Leader “Computational Image Analysis”, Center for Computational and Theoretical Biology, University of Würzburg

- 2012-2016 Postdoctoral Researcher and Lecturer in the Laboratory of Applied Mechanobiology (Chair: Prof. V. Vogel), ETH Zurich, Switzerland

- 2010-2011 Postdoctoral Researcher in the Department of Biomaterials (Chair: Prof. P. Fratzl) at the Max Planck Institute of Colloids and Interfaces, Golm, Germany

- 2006, 2007 Visiting Researcher in Department of Cell Biology (Chair: Prof. C. Waterman), Scripps Research Institute, La Jolla, USA

- 2004-2009 Doctoral thesis in the Biophysics Group (Chair: Prof. B. Fabry) of the Department of Physics at the University of Erlangen, Germany

Research synopsis

We are interested in how cell mechanics, cell-cell and cell-matrix interactions give rise to the complex dynamics of biological systems. By combining biophysics with high-end imaging and AI-based pattern recognition, we aim towards a quantitative understanding how cellular behavior and physical properties determine biological function.

This study is Project 14  of the SPP 2332 PoP.