Post-doc in Bioinformatics Laboratory: machine learning and docking for protease cleavage-site prediction

Postdoctoral position in the Bioinformatics Laboratory of the Mossakowski Medical Research Institute, Polish Academy of Sciences, in an NCN project led by Dr hab. Michał Koliński. Proteases drive protein activation and degradation, digestion and apoptosis, and their dysregulation makes them important therapeutic targets, yet current cleavage-site predictors rely mainly on substrate sequence and neglect the structure and dynamics of enzyme–substrate complexes.

The project integrates coarse-grained docking of enzyme–peptide complexes with machine learning: large sets of models for cleaved and non-cleaved peptides will train a scoring function that identifies cleavage sites from structural analysis, building on preliminary work with pepsin, renin and HIV-1 protease. Responsibilities include building a benchmark dataset, assessing ML-based protein structure prediction tools, implementing the trained scoring method and a prediction pipeline, developing the Dock-Cleave web service, and publishing and presenting results.

Full-time fixed-term contract of about two years from January 2027, paid under NCN rules. Applications (CV with publications, motivation letter, PhD diploma, referee contact) are emailed with the subject "Procedure ID: PBI.111.1.2026"; interviews are online and results are expected in December 2026.

PhD in chemistry, biology, computational sciences or a related field obtained no earlier than 12 years before employment (NCN exceptions apply); strong expertise in comparative modelling, molecular dynamics, ligand docking and protein structure prediction; documented experience with the CABS model and ML structure predictors such as AlphaFold-Multimer or AlphaFold3; molecular visualization tools; enzymology and proteolysis background; Python or C++; excellent English; JCR-listed publications.