Student for the project on deciphering protein evolution with the aid of machine learning

Opis:

 

Title of the position: Student

Scientific discipline: Bioinformatics

Job typeScholarship

Number of job offers: 1

Stipend amount/month: 1,500.00 PLN

Position starts on: 01.03.2019

Maximum period of contract/stipend agreement: 24

Institution:Laboratory of Structural Bioinformatics; https://lbs.cent.uw.edu.pl

Project leader: Dr. Stanisław Dunin-Horkawicz

Project description: The goal of the project is to infer a detailed evolutionary history of the Rossmann fold, which is one of the most prominent protein folds and by far the most functionally diverse one, with >300 different functions. To this end, we will perform a comprehensive bioinformatics analysis, with the aim of integrating data from different sources to obtain a reliable phylogenetic tree that encompasses all the major Rossmann enzymes classes. Unraveling the natural history of the Rossmann enzymes will open the possibility (i) to reveal the principles that governed the divergence of cofactor specificity of Rossmann enzymes, (ii) use these principles to rationally re-engineer cofactor specificity in Rossmann enzymes, and (iii) to identify the rudimentary Rossmann fold, and thereby design a functional minimal Rossman. The proposed project involves experimental validations, including structure determination of natural and re-engineered proteins together with the cofactors. The project includes collaboration with two partners: (i) Core Facility for Crystallography and Biophysics, University of Warsaw (Poland) and (ii) Department of Biomolecular Sciences, Weizmann Institute of Science (Israel).

Project clause: Project is carried out within the FIRST TEAM programme of the Foundation for Polish Science

Key responsibilities include:
Design and implementation of Machine Learning tools for protein sequence and structure analysis

Profile of candidates/requirements:
1. Should be enrolled as a student of bioinformatics, biology, biochemistry, biophysics or related discipline
2. Previous experience in Machine Learning (particularly TensorFlow and Keras packages). Good knowledge of Python. Experience with high-performance computing and Linux environment
3. Although not required, any previous experience in protein sequence and structure analysis would be beneficial
4. The candidate should be willing to learn new techniques and support the other group members
5. Good oral/written communication skills in English would be advantageous

Required documents:
1. A letter confirming that the candidate is currently enrolled as a Master’s student
2. A copy of a BSc certificate (if applicable)
3. CV (up to two A4 pages)
4. A cover letter (up to one A4 page)
5. Contact details of one academic researcher/teacher willing to provide a Recommendation letter for the Candidate

We offer:
1. An opportunity to participate in a multidisciplinary project conducted in a collaboration with scientists from Poland (University of Warsaw) and Israel (Weizmann Institute of Science)
2. Stimulating and friendly work environment
3. Access to to the high-end computing equipment (CPU and GPU clusters)
4. Participation in at least one scientific meeting

Please submit the following documents to: s.dunin-horkawicz@cent.uw.edu.pl

Project is carried out within the FIRST TEAM programme of the Foundation for Polish Science

To allow us to process your data, please include the following statement in your application:

“I hereby consent to have my personal data processed by the University of Warsaw with its registered office at ul. Krakowskie Przedmieście 26/28, 00-927 Warszawa for the purpose of carrying out a recruitment process and selecting an employee and concluding a contract for employment at the University of Warsaw. I have been informed of my rights and duties. I understand that provision of my personal data is voluntary.”

In accordance with Article 13 of REGULATION (EU) 2016/679 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data – general regulation on data protection (Official Journal of the EU L 119/1 of 4 May 2016) the University of Warsaw informs that:

  1. The administrator of your personal data is the University of Warsaw with its registered office at Krakowskie Przedmieście 26/28, 00-927 Warszawa, e-mail: iod@adm.uw.edu.pl;
  2. The Administrator has designated the Data Protection Officer who supervises the processing of personal data, and who can be contacted via the following e-mail address: iod@adm.uw.edu.pl;
  3. Your personal data will be processed for the purpose of carrying out a recruitment process and selecting an employee and concluding a contract for employment at the University of Warsaw;
  4. The provided data will be processed pursuant to Article 22(1) § 1 of the Act of 26 June 1974 Labour Code (uniformed text: Dz.U. of 2018, item 917) and your consent for processing of personal data;
  5. Provision of data in the scope stipulated in the Labour Code is mandatory (this is: name(s) and surname, parents’ first names, date of birth, address of residence, correspondence  address, education, previous employment);
  6. The remaining data are processed according to your consent for processing of personal data;
  7. The data will not be shared with any external entities, except for the cases provided for by law;
  8. The data will be stored until you withdraw your consent for processing of personal data;
  9. You have the right to access your personal data, rectify, erase, restrict its processing and to withdraw the consent at any time – the withdrawal of consent to processing data should be done in written form, acceptably by e-mail sent to hr@cent.uw.edu.pl;
  10. You have the right to lodge a complaint to the President of the Office for the Protection of Personal Data;
  11. Your application will be archived and stored for auditing purposes;
  12. The name of the selected candidate/s will be made public on the CeNT UW website in accordance with the requirements of the funding agency.

 



Termin nadsyłania aplikacji: 18/01/2019

Słowa kluczowe: bioinformatics, machine learning, protein evolution