DRT/LIST- CDD/POST DOC in biostatistic and bioinformatics: Innovative math.méthods

Vacancy details

General information

Organisation

The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.

Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.

The CEA is established in ten centers spread throughout France
  

Reference number

2019-9682  

process delay

3 months

Job details

Category

Information system

Contract

Post-doctorat

Job title

DRT/LIST- CDD/POST DOC in biostatistic and bioinformatics: Innovative math.méthods

Subject

biostatistics and bioinformatics: Innovative mathematical methods for the integration of omics data

Contract duration (months)

24

Job description

Context :
Proteomics and metabolomics provide unique and complementary information to decipher gene function and pathways, elucidate phenotypes, and robustly discover new biomarkers for disease treatments.
Integration of both approaches is a mathematical challenge because of the heterogeneity and the complexity of the proteomics and metabolomics data, and the partial annotation (i.e. metabolite identification) provided by the metabolomics mass spectrometry technologies.
The national infrastructures in bioinformatics (IFB), metabolomics (MetaboHUB), proteomics (ProFI), genomics (France Génomique), and mouse phenogenomics (PHENOMIN) have decided to join forces and develop new biostatistics and bioinformatics methods and tools for high-throughput and combined proteomics and metabolomics data analysis.

Project :
First, statistical modeling will be used to explore the specific and common information from each type of omics data, and to determine how their combination as molecular signatures can optimally be used to interpret and predict the phenotypes. Such approaches will include linear and nonlinear methods for multivariate analysis.
Second, network integration will be used to facilitate interpretation and annotation of the data. Proteins and metabolites will be mapped on the metabolic networks to facilitate chemical annotation and biological interpretation, and to suggest new biomarkers and metabolic functions.
The mathematical approaches and tools will be validated on two use cases: 1) the high-throughput molecular phenotyping of comprehensive collections of mouse models and 2) the discovery of new gene functions in a bacterial model of interest for environmental and biotechnological applications.

Applicant Profile

Interested applicants should have a strong background in statistics (data analysis, network analysis), and be motivated by multidisciplinary applications (chemistry, biology, clinic).

Job location

Site

Saclay

Location

Route du Cyclotron, 91400 Saclay, France

Candidate criteria

PhD opportunity

Non