Sano PhD students

Project title: Application of biclustering and artificial intelligence to the analysis of biological and medical data

Give us a chance to meet you

Sano Centre for Computational Medicine is a new International Scientific Foundation located in Kraków, Poland.

Sano aspires to be a major translational scientific institute, operating at the meeting point of academic science, established MedTech industry, and emerging start-up environment, combining the best of these three perspectives.

Sano acts as a core technology and expertise provider for industry, and creator of innovation, developing state-of-the-art solutions for healthcare. Thanks to the substantial funding and excellent European partnership network, Sano will bring a critical mass to this transformational field of research, in order to translate scientific advancements onto clinical practice. Sano’s ambition is to become the Reference Centre for Computational Medicine in Central Europe and build a reputation as a leading institute on a global level.

As a cross-disciplinary institution, Sano uses machine learning/artificial intelligence (ML/AI), large scale computer simulations (HPC), data science, and other computational technologies towards overcoming global challenges in healthcare systems. The research agenda will be executed in close collaboration with Partners in Poland, EU and USA.

We value:

  • Passion – Passion in what we do, engagement in Sano operations, taking responsibility, providing initiative, being happy at work.
  • Innovation – Boldness in articulating and pursuing novel ideas, courage to think outside the box.
  • Integrity – Directness, openness, tolerance and respect. Scientific integrity (we do not cut corners).
  • Diversity – Diversity in backgrounds, cultures and opinions of Sano employees. Promotion of women in STEM.


  • AGH: Dr. Jarosław Wąs (1st supervisor)
  • University of Pennsylvania: Dr. Patryk Orzechowski (2nd supervisor)
  • Sano: Research Group Leader

One of the pattern recognition methods derived from clustering is biclustering, a modern technique of data mining. It is widely used, especially in the study of gene expression. Contrary to the classic clustering algorithms, in biclustering, the classification takes place while taking into account the features and their values, which correspond to the rows and columns of the input matrix. This makes it possible to identify similarities locally (i.e., subsets of rows similar across subsets of columns), not only globally.

This project focuses on designing highly efficient biclustering techniques and improving existing ones with particular emphasis on the use of modern parallel architectures, integrating multiple data sources, as well as exploring new areas of application of artificial intelligence in the biomedical domain.

This project aims at the development of a wider family of biclustering methods deriving from EBIC and artificial intelligence approaches. The main activities planned within this project involve the following:

  • EBIC with expert knowledge
  • Analysis of Electronic Health Record with biclustering
  • Classifier based on EBIC with SHAP values
  • 2-step EBIC
  • Integration of multi-omics data with EBIC
  • EBIC improvements, using parameter tuning and adjusting to the analysis of scRNAseq and RNAseq
  • Application of EBIC-derived solutions to disease data
  • Crawler seeking genomical/disease data
  • Data integration, reproducibility and prevalence across multiple datasets
  • Analysis of data annotations
  • Using deep learning for analysis of medical records

You are expected to:

  • do original research in this field under the direction of the supervisor;
  • participate in the many seminars by internal and external speakers as well as journal clubs and group activities;
  • collaborate with other PhD candidates, postdoctoral researchers and other Sano employees.

Required background and skills of the candidate:

  • Master’s degree (completed or near completion) in a relevant discipline, such as computer science, biomedical engineering, etc;
  • knowledge of AI and machine learning methods, biclustering, programming skills (Python);
  • any prior research experience in academia or industry;
  • an interest in pursuing applied research.

We offer a fixed term contract for 40 hours per week for the duration of 4 years. This will be supported by an educational plan that includes attendance of courses and (international) meetings. The contract will include opportunities to participate in teaching and supervision of undergraduate and master students.

The salary, depending on relevant experience before the beginning of the employment contract, will be up to 8000 PLN gross per month, based on a full-time contract (40 hours a week) for the duration of 4 years with private medical care and a sports card.

This PhD will be a collaboration between Sano and AGH. AGH will be the degree awarding body. The student will be based in Poland, operating in conjunction with the Cyfronet supercomputing centre hosted by AGH.

Sano offers excellent opportunities for study and development, an access to many international conferences on computational medicine and a possibility to grow in a scientific society.

If you feel that this job opportunity is the career that you are looking for, please apply immediately and give Sano a chance to meet you. Please, be informed that Sano will contact only with Candidates fulfilling the formal criteria.

Sano is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.

Do you recognize yourself in the job profile? Then we look forward to receiving your application.

Applications in .pdf should include:

  • a cover letter;
  • a curriculum vitae;

Apply through Sano recruitment system. If you would like to apply for future openings feel free to send your application to our database.​