Job Information
- 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.[contact details available in the full listing]
- 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 of identification of proteolytic cleavage sites in peptide substrates using coarse-grained docking and machine learning methods.
Project description:
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.
Where to apply
E-mail: [contact details available in the full listing]
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 — Excellent; Polish — Good
Research Field: Biological sciences, Chemistry, Computer science
Internal Application form(s) needed: Application Information_PBI.[contact details available in the full listing]_PostDoc.pdf (English, 75.93 KB - PDF)
Additional Information
Benefits
- employment at one of the leading scientific institutions in Poland;
- employment contract (full-time) for fixed term (ca 2 years);
- salary in line 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.
Selection process
Please download the file attached under 'Internal Application form(s) needed'. It contains the detailed application guidelines, list of required documents and the mandatory GDPR clause.
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
Contact
- City: Warsaw
- Website: http://imdik.pan.pl
- Street: 5 Pawinskiego Street
- Postal Code: 02-106
