PhD student position at the Department of Chemistry, Faculty of Science, Lund University.
Subject description
The project aims to better understand how conformational changes are encoded in protein sequences, and to develop new methodology to predict conformational diversity and changes using machine learning. With the help of deep-learning approaches methods to predict flexibility, conformational changes, and structural ensembles will be developed. The project may also involve application of the methodology in the computational design of proteins with the ability to sample conformational states. The methodology can involve the utilization of generative models to sample protein structures, extension of deep-learning frameworks for protein structure prediction, language models and algorithms for morphing and clustering. The recruited candidate will be enrolled in a graduate school in machine learning through WASP.