Postdoctoral researcher in sequence-based protein coevolution (R2)

Job Reference

108_21_LS_CB_R2

Position

Postdoctoral researcher in sequence-based protein coevolution (R2)

Closing Date

Friday, 16 April, 2021
Reference: 108_21_LS_CB_R2
Job title: Postdoctoral researcher in sequence-based protein coevolution (R2)

About BSC

The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, and is a hosting member of the PRACE European distributed supercomputing infrastructure. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 700 staff from 49 countries.

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Context And Mission

The Computational Biology group, led by ICREA professor Alfonso Valencia, is looking for a postdoctoral researcher to work in the context of sequence-based protein coevolution.

The Life Sciences Department at the BSC integrates the independent research of senior scientists that work on various aspects of computational biology, ranging from bioinformatics for genomics to computational biochemistry and text mining. The Computational Biology group (http://life.bsc.es/compbio) is involved in multiple projects covering a wide range of topics including multilayer network modeling, epigenomics and computations systems biology. Recently the Computational Biology group has joined a consortium along with the Animal Health Research Center (CReSA) of the Institute of Agrifood Research and Technology (IRTA) and the IrsiCaixa AIDS Research Institute, funded with the support of Grifols. The consortium's strategy is to generate the vaccine using VLPs (virus-like particles), which have the same structure as a virus but without being infective. Researchers are designing these VLPs using the protein S of the SARS-CoV-2 on its surface.

The candidate will work in collaboration with senior researchers in the Computational Biology Group of the Life Sciences Department as well as other research groups at the BSC. The work is in the framework of the research lines of the group, involving in personalized medicine, and sequence-based protein coevolution.

The Researcher will work in a highly sophisticated HPC environment, will have access to state-of-the-art systems and computational infrastructures, and will establish collaborations with experts in different areas both at international and local levels, in particular. The Researcher’s tasks will involve applying co-evolutionary methods for sequence-based prediction of structural contacts, protein-protein interfaces, specific protein partners and the effect of single or multiple amino acid mutations in the stability of protein structures.

Key Duties

  • Deployment of state-of-the-art coevolution-based methods for the study of relevant biological problems involving proteins.
  • Perform sequence-based analysis of viral proteins to improve the understanding of important host-pathogen protein-protein interactions.
  • Investigate protein-protein interaction networks in different organisms using coevolution-based approaches.

Requirements

  • Education
    • PhD in computer science or bioinformatics (or equivalent).
  • Essential Knowledge and Professional Experience
    • Experience in protein sequence analysis
    • Knowledge of coevolution-based methods applied to protein sequences (MI, DCA, EVcouplings)
  • Additional Knowledge and Professional Experience
    • Knowledge of multivariate statistics and information theory
    • Knowledge and experience in structural analysis (pymol, vmd, quimera)
    • Knowledge and experience in phylogenetics
    • Programming: Python (numpy, scipy, matplotlib, biopython), Matlab, R, C++, Git
  • Competences
    • Fluency in spoken and written English
    • Good communication and presentation skills
    • Ability to work both independently and within a team

Conditions

  • The position will be located at BSC within the Life Sciences Department
  • We offer a full-time contract, a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, tickets restaurant, private health insurance, fully support to the relocation procedures
  • Duration: Temporary - 1 year renewable
  • Salary: we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona
  • Starting date: may 2021

Applications Procedure

All applications must include:

  • A Cover Letter with a statement of interest in English, including two contacts for further references - Applications without this document will not be considered

  • A full CV in English including contact details


Deadline

The vacancy will remain open until suitable candidate has been hired. Applications will be regularly reviewed and potential candidates will be contacted.

Diversity and Equal Opportunity Employment

BSC-CNS is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or any other basis protected by applicable state or local law.

Application Form

Please, upload your CV document using the following name structure: Name_Surname_CV
Files must be less than 3 MB.
Allowed file types: txt rtf pdf doc docx.
Please, upload your CV document using the following name structure: Name_Surname_CoverLetter
Files must be less than 3 MB.
Allowed file types: txt rtf pdf doc docx zip.
Please, upload your CV document using the following name structure: Name_Surname_OtherDocument
Files must be less than 10 MB.
Allowed file types: txt rtf pdf doc docx rar tar zip.
** Consider that the information provided in relation to gender and nationality will be used solely for statistical purposes.