Physics of Biological and Complex Systems (IMPRS)

The GGNB doctoral program / International Max Planck Research School "Physics of Biological and Complex Systems" is a member of the Göttingen Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences (GGNB). It is conducted jointly by the University of Göttingen, the Max Planck Institute for Multidisciplinary Sciences, and the Max Planck Institute for Dynamics and Self-Organization.

The research-oriented program is taught in English and open to students who hold a Master's degree (or equivalent) in the physics, biophysics, chemistry, life sciences or related fields.

Building upon the existing strong links between the involved Faculties and Institutes, two lines have emerged. First, the demand to raise biological research towards a more quantitative level implied an increasing need for biophysical methodology both at the molecular and the cellular levels. Second, the increasingly accurate characterization of many biological systems (such as biomolecules, intermolecular networks, and strongly interacting cellular networks) represent, from a physics point of view, non-equilibrium, highly nonlinear, and strongly interacting systems, where new phenomena and new physics emerge.

More recently, links have been established and strengthened both between biological and complex systems questions, e.g., on the level of complex networks or heterogenuous and active matter, as well as between biophysics and applied mathematics.

On the imaging side, nano-scopy, X-ray imaging and diffraction, and single molecule spectroscopy are an essential element of the IMPRS. At the atomic level, X-ray crystallography, electron microscopy, EPR, fluid, and solid state NMR probe biomolecular structure and dynamics.

Theory and numerical simulations constitute an integral part of the IMPRS. Mathematical approaches and atomistic or coarse-grained simulations reveal functional details that can be compared to experiments, explain experiments at the atomistic level, or may be even stand-alone results in cases where experiments are currently not possible. Similarly, mathematical models of cytoskeletal, chemical network or self-organizing dynamics make testable quantitative descriptions and help to understand shortcomings in our biological understanding.