Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Position in the project Interpretable and Interactive Multimodal Retrieval in the Drug Discovery Process.
Project is being carried out within the First Team FENG programme of the Foundation for Polish Science.
The drug discovery process is complex, requiring substantial financial investment and many years of work to bring a new drug to market. One way to shorten the time and reduce the costs of this process is through artificial intelligence. This approach can reduce the number of failures in clinical trials and facilitate the exploration of the chemical compound space. In this project, we propose utilizing tools based on knowledge retrieval and interactive, interpretable machine learning to increase the efficiency of the drug discovery process. The developed tool will be able to analyze images of cellular events, such as those obtained in the CellPainting (CP) protocol, and identify potential small-molecule drugs that can induce specific cellular events. It will make drug discovery, such as hit identification, virtual screening, and drug repurposing, faster and more cost-effective.
We will collaborate with Matthias Zeppelzaur, an expert in knowledge retrieval, and Ardigen SA, a global leader in AI-based services for pharmaceutical companies. Ardigen also develops phenAID software, which enables advanced analysis of images obtained using the CP protocol.
Where to apply
E-mail: dorota.ramotowska@uj.edu.pl
Requirements
Research Field: Computer science
Education Level: Master Degree or equivalent
Skills/Qualifications
- Planning and conducting computational experiments on deep learning for multimodal retrieval;
- Implementing novel training techniques and interpretable models;
- Identifying suitable regularization techniques for the specific problem;
- Analyzing and visualizing results;
- Preparing manuscripts;
- Presenting scientific data at international conferences.
Specific Requirements
- MSc degree in Computer Science or similar;
- PhD student status required during the contract period;
- Experience in information retrieval or explainable artificial intelligence;
- Practical experience in the analysis of scientific data;
- Proficiency in programming with Python;
- Familiarity with the concepts in multimodal information retrieval;
- Ability to work on interdisciplinary projects;
- Fluency in both written and spoken English.
Languages: ENGLISH
Level: Excellent
Research Field: Computer science
Additional Information
Benefits
- A 23-month scholarship, subject to periodic evaluation;
- Scientific and organizational support;
- Opportunities to work within an interdisciplinary research team publishing in top-tier conferences and journals (see https://gmum.net/).
Eligibility criteria
- Motivation letter;
- Curriculum vitae;
- Documents verifying experience and background;
- Recommendation from a scientific supervisor.
Selection process
- Candidates may apply simultaneously for all positions offered by the project, but it must be indicated on the application form.
- The decision will be made by the Recruitment Committee of the Faculty of Mathematics and Computer Science at the Jagiellonian University.
- The Recruitment Committee reserves the right to invite only selected candidates for an interview, which take place on October 14, 2026.
- The Recruitment Committee also reserves the right to close the competition without selecting a candidate.
- The results of the competition will be announced before October 31, 2026.
Additional comments
Remuneration: 5000 PLN net per month.
Position starts on: not earlier than 1st November 2026.
Maximum period of contract/scholarship agreement: 23 months.
Project leader: Bartosz Zieliński.
For more details about the position please visit: https://xaipaint.matinf.uj.edu.pl/.
Work Location(s)
- Number of offers available: 1
- Company/Institute: Faculty of Mathematics and Computer Science
- Country: Poland
- State/Province: Malopolska
- City: Krakow
- Postal Code: 30-348
- Street: ul. Łojasiewicza 6
Contact
