Job Location
69007 LYON
Job Description

— Permanent position – based in Lyon


The Technological Unit “Management and Data analysis” has to develop technologies and solutions allowing to collect, follow, analyze, visualize and exploit the data generated by the experimental devices of the others BIOASTER units: genomics, transcriptomics, proteomics, metabolomics, cytometry, imaging, etc.

BIOASTER has also other sources of information from preclinical or clinical studies.

The candidate will :

Develop the processes allowing a global analysis of the genomics, transcriptomics, proteomics, metabolomics, cytometry results, in association with the appropriate units,

Contribute to the automation and the integration of these processes at the heart of the Scientific Information system and the bio-computing platforms of BIOASTER,

Propose a methodological jump concerning the statistical analysis of high dimensional data – from multi-omics, phenotypic and/or clinical origin - to bring strong and innovative answers to translational sciences issues of the TRI , e.g the identification of biomarkers or the characterization of mechanisms of action, by taking more particularly into account the duality and the complexity of host-pathogen systems.


In collaboration with the bioinformatics community of BIOASTER, realize the state of the art and estimate the methods regarding integrative analyses of genomic, transcriptomic, proteomic and metabolomic data, as well as to contribute to their developments,

In association with the bioinformatics community of BIOASTER, participate in the evaluation of the statistical methods for the transformation, the standardization and the integration of the data (omics, phenotypic or clinical),

Contribute to the analysis of data generated in collaborative projects led by BIOASTER with industrial, academic or SME partners,

Participate in the evolution of the data management, the data analysis and the data visualization operated by the bioinformatics platform, or other services managed by the team.




Skills :

Master degree level or / and PhD, engineering school or equivalent in statistics or bioinformatics, with 3 - 5 years of experience in a similar function in an academic or biotech/industrial Life Sciences environment,

Good knowledge of R,

Very good knowledge of supervised learning (support vector machine, random forest) ;

Very good knowledge of the multivariate statistical methods (principal component analysis, independent component analysis, correspondence analysis, correspondence canonical analysis and associates regularization methods, partial least square regression, clustering),

General knowledge of data processing and analysis in the bioinformatics area,

Good knowledge of Bourne Shell, Python,

General knowledge of GNU/Linux (Red Hat, CentOS, Scientific Linux),

General knowledge of software engineering methods and project management,

Knowledge of an EDI and a source version control system to operate in a collaborative/concurrent context,

Scientific and technological English language proficiency



Personal qualities

  • Autonomy, thoroughness, reactivity,
  • Initiative Spirit and creativity,
  • Team spirit in project mode,
  • Good communication and interpersonal skills,
  • Confidentiality and regulatory compliance
  • Quality and GxP oriented

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