Project title: Evolutionary-scale interpretation of protein functions in the human gut microbiome – NCN Weave
Publication date: 24.07.2025
Closing date: 7.08.2025, results published 23.09.2025
Level of education: Master’s degree, enrollment at a doctoral school
Hours: 40 hours per week (in total, including employment at Sano and enrollment at a doctoral school)
Salary indication: up to 5000 PLN gross gross (employer’s costs)
Supervisors:
Sano: dr. Tomasz Kościółek (Structural and Functional Genomics Research Group Leader)
Project start: 1.10.2025
Recently, deep learning has caused a revolution in the field of computational biology. By learning from the wealth of protein information deposited in various protein databases, it has allowed the development of multiple computational tools for the analysis of such proteins. By applying deep learning methods to predict the three-dimensional structures of proteins at unprecedented levels of accuracy, researchers can now study the functions and interactions of proteins that have no known homologs. In the protein sequence space, by treating proteins as strings of words, deep learning models can detect evolutionary relationships that were previously out of reach, allowing for the annotation of remote homologs and orphan genes. To better understand what proteins do functionally, combining sequence and protein 3D structure information within deep learning algorithms, unlocked access to vast functional repertoire encoded in proteins. This is thus the right time to carry out a large-scale analysis of these proteins, combining deep learning based methods for protein structure prediction, the detection of very distance evolutionary relationships and function predictions, beyond the ability of standard approaches.
In this project, we will create an atlas of human gut protein structures annotated with functions and a protein universe map to help us navigate this vast space. We will use deep learning and largescale evolutionary modeling to better understand the functionally dark proteins of the human gut metagenome. By studying the proteins and their genomic context, we will seek to identify unique proteins and their potential roles in human health and behavior. Our findings will help to prioritize future research and provide a more comprehensive view of the proteins found in the human gut.
Please note, the project is fully computational and does not involve any experimental (laboratory) work.
What are you going to do?
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.
What do we require?
As our successful candidate you should have:
- experience in programming (esp. Python);
- some experience in bioinformatics;
- interest in deep learning techniques;
- interest in microbiome research;
- interest in molecular evolution;
- you need to be enrolled at a doctoral school.
Our offer
The position is funded for up to 4 years with an expected start date on 1.10.2025. 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.
This PhD will be a collaboration between Sano and AGH. The student will be based in Poland, Krakow 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.
Questions?
Do you have questions about this vacancy? Or do you want to know more about our organisation? Please contact us at talents@sano.science
About Sano
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.
Established with support from the European Commission and the Foundation for Polish Science, Sano aims to be a major driving force behind the advancement of computational medicine for the benefit of healthcare systems worldwide.
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.
Job application
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;
The recruitment process will involve an interview with a Recruitment Committee of at least two senior researchers at Sano and a separate competency-based interview with the Team Leader, discussing a provided scientific paper.
Apply:
https://sano.elevato.net/en/sano-phd-student-ncn-weave,ja,185
https://euraxess.ec.europa.eu/jobs/363533