Habeck, Michael, Dr.

1993-1999: Physics studies at the University of Siegen and the University of Heidelberg
2001-2004: PhD work at Institut Pasteur, Paris
2004-2005: Postdoc Institut Pasteur, Paris
2005-2009: Research scientist at the Max-Planck-Institute for Biological Cybernetics and the Max-Planck-Institute for Developmental Biology, Tübingen
2009-2012: Leader of an independent research group (Emmy Noether Programme) at the Max-Planck-Institute for Developmental Biology, Tübingen
2013-2014: Leader of an independent research group (Emmy Noether Programme) at the University of Göttingen
since 2015: Project leader at Max Planck Institute for Biophysical Chemistry and University of Göttingen

Major Research Interests
I am broadly interested in Bayesian inference and its application to biological and other real- world data. I view probability theory as the mathematical framework for making consistent inferences and predictions from incomplete and uncertain information. Therefore, Bayesian methods are powerful tools to support scientific inference and to solve engineering problems. My previous and current research focuses on three highly interconnected topics: Computational structural biology, Bayesian computation and Statistical physics.
My group is mainly involved in the development of a Bayesian probabilistic approach to biomolecular structure determination which we call Inferential Structure Determination (ISD). Over the years, ISD has matured into a powerful tool for macromolecular structure calculation from NMR, X-ray, cryo-EM and other structural data by means of Markov chain Monte Carlo simulation. Moreover, we maintain a keen interest in developing new methods for cryo-EM data analysis and image processing. We are currently developing tools to model large and dynamic systems (protein complexes, chromosomes) and work on new algorithms for general Bayesian computation.

Homepage Department/Research Group
http://www.stochastik.math.uni-goettingen.de/habeck

ORCID: 0000-0002-2188-5667