PhD Positions in Computational Structural Biology University of Göttingen, Germany
We are looking for talented, highly motivated and self-driven candidates to pursue a PhD in computational structural biology. The projects revolve around method development for modeling macromolecular complexes from hybrid experimental data and are part of a collaborative research consortium (CRC 860) that provides a platform for interaction with leading experimental groups.
The PhD projects will be part of an effort to develop statistical and computational tools for characterizing the structure and dynamics of large macromolecular complexes. Structural information on macromolecular complexes can be obtained through an array of experimental techniques including X-ray crystallography, solution and solid-state NMR, cryo-EM, small-angle X-ray scattering and cross-linking/mass spectrometry. These methods provide data of varying quality and information content. Typically the data are by themselves not sufficient to determine an atomic structure. Therefore, the integration of heterogeneous data is often the only practical approach to characterize the structure of a macromolecular complex. We aim to use Bayesian inference to develop a robust and versatile computational tool for combining diverse structural data in order to determine the three-dimensional structure of biomolecular complexes.
Candidates should have a background in at least one of the following fields: Theoretical, Statistical and/or Computational Physics, Bioinformatics, Biophysics, Statistics, Bayesian Inference, Applied Computer Science. The project will require mathematical and programming skills (Python, C). The successful candidates will join the Computational Structural Biology group at the Institute for Mathematical Statistics (University of Göttingen, Germany) and the Max Planck Institute for Biophysical Chemistry. Göttingen offers a unique scientific environment with many excellent experimental and theoretical groups in Structural Biology and Biophysics. Various doctoral programs offer support for PhD candidates.
Contact: Michael Habeck, Institute for Mathematical Stochastics, University of Göttingen, This email address is being protected from spambots. You need JavaScript enabled to view it.
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