Sano PhD Student - Evolutionary-scale interpretation of protein functions in the human gut microbiome – NCN Weave

Region / State / Province małopolskie
About job:

Sano PhD Student 

Project title: Evolutionary-scale interpretation of protein functions in the human gut microbiome – NCN Weave 

Publication date: 19.07.2024 

Closing date: 18.08.2024, results published 1.09.2024 

Level of education: Master's degree, enrollment at AGH doctoral school 

Hours: 40 hours per week 

Salary indication: up to 5000 PLN gross gross (employer’s costs) 

This is a competition for NCN stipend (stypendium naukowe NCN), the competition is held in accordance with relevant rules available here: 

Supervisors:  

Sano: dr. Tomasz Kościółek (Structural and Functional Genomics Research Group Leader)  

AGH: dr. Maciej Malawski 

Project start: October 2024 

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. 

Link to apply to AGH doctoral school: 
Key tasks:

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; 

  • be enrolled in AGH Computer Science doctoral school. 

Our offer:

The position is funded for up to 4 years with an expected start date in October 2024. 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. The candidate must be enrolled at AGH doctoral school. 

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. 

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Last modified Thursday, July 18, 2024
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