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Portail > Offres > Offre UMR5095-KILAUD-002 - Chercheur postdoctoral en biologie computationnelle H/F

Postdoctoral Researcher in Computational Biology H/F

This offer is available in the following languages:
Français - Anglais

Date Limite Candidature : mardi 20 décembre 2022

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General information

Reference : UMR5095-KILAUD-002
Workplace : BORDEAUX
Date of publication : Monday, November 14, 2022
Type of Contract : FTC Scientist
Contract Period : 18 months
Expected date of employment : 1 January 2023
Proportion of work : Full time
Remuneration : between 2805.35 and 4140.29 euros gross per month depending on experience
Desired level of education : PhD
Experience required : 1 to 4 years


The postdoctoral fellow in computational biology will be responsible for developing software and open science for cancer.


The postdoctoral researcher will specifically contribute to the advancement of cancer data analysis portals - goal of the WP3 in the project. The work will be based on existing computational methods served in the form of software containers interoperable in Virtual Research Environments (VRE) and workflow managers (i.e., Galaxy : https://usegalaxy.eu). The use of community adopted platforms, cBioPortal (https://www.cbioportal.org) and the Clinical Decision Support Systems (e.g. MTBP, https://mtbp.org/ExamplePublic.php or PCGR https://github.com/sigven/pcgr), will make the operations of the underlying software layer transparent to the users.


We are looking for a highly motivated individual who has a passion for driving science through technology, has a strong taste for teamwork, and excellent communication skills that will thrive in our team to deliver best results. A successful candidate will have the following skills or experience:
- Ph.D. degree in Bioinformatics, Computer Science, Biostatistics, Applied Mathematics or related discipline.
- Hands-on experience in processing and analyzing Next Generation Sequencing data (DNA-Seq & RNA-Seq) for health-related applications.
- Understanding of main cancer data analysis (e.g. variant calling and annotation, biomarker identification)
- Proficiency in Python and R.
- Prior experience in software development.
- Knowledge of pipeline managers/workflow systems (e.g. Galaxy, Snakemake)
- Docker and/or Singularity experience
- Experience in machine learning would be a plus.

- Candidates must have a very positive attitude to working in a collaborative trans-border project.
- Finally, fluency in spoken and written English is a requirement.(C2 to C1 of the European Framework of Reference for Languages)

Work Context

EOSC4Cancer research and innovation action aims to connect a set of interoperable nodes, e.g. European Cancer Centres, Research Infrastructures, Medical Centres, that provide access to FAIRified cancer-related data within (a) trusted users environment(s). The selection of data and their connectivity will be driven by key use-cases that demonstrate the value at all stages along the cancer patient journey, and served in the visualization and analysis environments they are familiar with.
This project aims to make cancer genomics, imaging, medical, clinical, environmental and socio-economics data accessible, using and enhancing existing federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR cancer data across borders, and it will offer them via community-driven analysis environments. EOSC4Cancer provision of well curated datasets will be essential for advanced analytics and computational methods to be reproducible and robust, including machine learning and artificial intelligence approaches. EOSC4Cancer use-cases will cover the patient journey from cancer prevention through to diagnosis and treatment, laying the foundation of data trajectories and workflows for future cancer mission projects.

The postdoctoral researcher will work in the “Computational Biology and Bioinformatics” team (IBGC, CNRS, Bordeaux - France) under the supervision of Macha Nikolski (WP3 co-lead). Strong collaboration with other teams within the project is expected, in particular with the team of Pr. Eivind Hovig, University of Oslo (co-lead of WP3).

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