POST-DOC in Bioinformatics Laboratory

Mossakowski Medical Research Institute, Polish Academy of Sciences; Polska; On-site; PLN 110,000 - 150,000; Full time

Benefits offered by this job

Specialist equipment access

Social fund support

PPK participation

Group life insurance

Medical service package

Multisport card

Job summary

Mossakowski Medical Research Institute, Polish Academy of Sciences in Warsaw seeks a PhD-level researcher to develop a novel method for identifying proteolytic cleavage sites in peptide substrates by integrating structural modeling of enzyme–substrate complexes with machine learning.

The project generates large enzyme–peptide complex models to train a scoring function using ML, distinguishing cleaved vs non-cleaved substrates.

Qualifications

• PhD in Chemistry, Biology, Computational Sciences, or a related field.
• Strong expertise in molecular modeling: comparative modeling, MD simulations, ligand docking, and protein structure prediction.
• Experience with CABS model and ML for protein structure prediction (e.g., AlphaFold-Multimer).
• Proficiency with molecular visualization tools (VMD, PyMOL, Chimera, YASARA).
• Background in protein modeling, enzymology, proteolysis, sequence alignment, and docking.
• Excellent command of English (spoken and written).
• Programming skills in Python or C++.
• Publications and conference abstracts.

Skills

PhD in Chemistry,Biology,Computational

Molecular modeling

CABS model & ML methods

Molecular visualization tools

Protein modeling & docking

English proficiency

Programming: Python or C++

Publications & abstracts

Education

PhD or equivalent

Tools

AMBER

Modeller

ClustalW

MOE

CABS-dock

AutoDock

GOLD

Job description

Mossakowski Medical Research Institute, Polish Academy of Sciences

Organisation/Company Mossakowski Medical Research Institute, Polish Academy of Sciences Department

Department of Neurogenetics and Functional Genomics Research Field Biological sciences » Other Chemistry » Other Computer science » Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 21 Nov 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number PBI.111.1.2026 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

This position is related to the National Science Center (NCN) research project ofidentification of proteolytic cleavage sites in peptide substrates using coarse-grained docking and machine learning methods

Proteolytic enzymes (proteases) play a key role in numerous biological processes, such as protein activation and degradation, digestion, and apoptosis. Dysregulation of their activity is associated with numerous diseases, making proteases important therapeutic targets. Accurate identification of substrate cleavage sites is essential for understanding enzyme specificity and designing novel inhibitors. Currently available methods for predicting cleavage sites rely primarily on the analysis of substrate amino acid sequences, largely neglecting the structural and dynamic aspects of enzyme–substrate interactions.

The aim of this project is to develop a novel method for identifying cleavage sites in peptide substrates by integrating structural modeling of enzyme–substrate complexes with machine learning algorithms.

During the project, large datasets of enzyme–peptide complex models will be generated for both peptides that are cleaved by a given enzyme and those that are not. These models, capturing subtle differences in the binding modes of cleaved and non‑cleaved substrates, will subsequently be used to train a scoring function using machine learning methods. Cleavage sites in a given peptide will be identified through structural analysis of the generated enzyme–substrate complex model using an appropriately parameterized scoring function. Preliminary studies conducted for pepsin, renin, and HIV-1 protease have confirmed the effectiveness of this approach in predicting cleavage sites and revealed differences in the binding modes of cleaved and non‑cleaved substrates.

The developed method will provide a better understanding of the mechanisms of substrate recognition and protease specificity, as well as help identify structural factors influencing enzymatic activity.

Requirements

Research Field Biological sciences » Biology Education Level PhD or equivalent

Research Field Chemistry » Computational chemistry Education Level PhD or equivalent

Skills/Qualifications

• PhD in Chemistry, Biology, Computational Sciences, or a related field;
• strong expertise in molecular modeling methods, including comparative modeling, molecular dynamics simulations, ligand docking, and protein structure prediction;
• documented experience with the CABS model and machine learning approaches for protein structure prediction (e.g., AlphaFold-Multimer, AlphaFold3);
• proficiency in one or more molecular visualization tools (e.g., VMD, PyMOL, Chimera, YASARA);
• background in protein modeling, enzymology and proteolysis, sequence alignment, and ligand docking;
• excellent command of spoken and written English;
• good programming skills in at least one of the following languages: Python or C++;
• documented scientific achievements, including peer-reviewed publications (JCR-listed) and conference abstracts.

Specific Requirements

• experience using AMBER for molecular dynamics simulations;
• scientific publications in the field of molecular modeling;
• experience with molecular modeling tools such as Modeller, ClustalW, MOE, CABS-dock, AutoDock, or GOLD.

Languages ENGLISH Level Excellent

Languages POLISH Level Good

Research Field Biological sciencesChemistryComputer science

Internal Application form(s) needed

• employment at one of the leading scientific institutions in Poland;
• employment contract (full-time) for fixed term (ca 2 years);
• salary in line with with National Science Center (NCN) rules;
• access to specialist equipment in the Institute;
• additional support from the social fund (i.e. support in difficult life situations, childcare subsidies and low interest loans);
• possibility to join Employee Capital Plans (PPK);
• additional benefits such as opportunity to join a group life insurance program, medical service package, and a Multisport card on preferential terms.

Work Location(s)

Number of offers available 1 Company/Institute Mossakowski Medical Research Institute, Polish Academy of Sciences Country Poland State/Province Mazovian City Warsaw Postal Code 02-106 Street Pawinskiego 5 Geofield