The Ph.D. student position is offered under the project entitled „Statistical Learning of Slow Collective Variables from Atomistic Simulations,” led by Dr. Jakub Rydzewski at the Institute of Physics, Nicolaus Copernicus University in Toruń, Poland. The project is financed by National Science Center in Poland (Sonata).
Modeling the long-timescale dynamics of biophysical and molecular systems is a fundamental task in the physical sciences. Molecular dynamics (MD) simulations enable studying complex processes on microscopic spatiotemporal scales. However, such complex processes are often characterized by thousands of degrees of freedom which is very difficult to analyze in practice.
In this project, a machine-learning method will be devised to select a small number of physically-valid degrees of freedom in a near-blind manner improving the analysis of MD simulations. This method will be applicable to long-timescale processes in chemistry, physics, and biology.