We are currently looking for Master’s students with a background in machine learning (or related computational field) for a project on Protein Fitness Optimization.
Protein fitness optimization aims to improve a protein’s functionality by modifying its amino acid sequence to enhance a specific property, such as stability or binding affinity. There are various computational approaches to tackle this problem that enable in-silico pipelines to suggest new protein candidates. One of them involves generative models, which aim to capture the distribution of protein sequence data and propose new sequence mutants based on the learned distribution.