01/06/2018

PhD in Data Science: Integrative clustering and informed source separation of multi-omics and multi-species (genomic, transcriptomic, epigenetic) data


  • ORGANISATION/COMPANY
    IFP Energies nouvelles (former Institut Français du Pétrole – IFP)
  • RESEARCH FIELD
    Computer science
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    15/09/2018 23:00 - Europe/Athens
  • LOCATION
    France › Rueil-Malmaison
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35
  • OFFER STARTING DATE
    01/10/2018
  • REFERENCE NUMBER
    2018-R11-06

The study and the adaptation of micro-organisms to the domain of agrofuels and green chemistry aim at conceiving and controlling potential microbial factories. They are piloted by their genome expression, with very diverse mechanisms, sensitive to external conditions (environment, temperature, nutrients). They form complex systems, highly integrated, requiring information at different levels. The eruption of novel high-throughput experimental technologies, combined with an increased access to experimental data, have demultiplied the available data and means of optimization for the studied systems. Algorithmic tools, in a wide sense, leverage visualization, transformation and prediction, turning multiple, heterogeneous and incomplete data into added information and usable knowledge. This subject is inscribed in the field with fuzzy borders of bioinformatics, systemic or in silico biology, and data science.

The main objective of this subject is to offer an improved understanding of the different regulation levels (from model organisms to Trichoderma reesei strains), throught data integration from different biological mechanisms and strains, combining genome, transcriptome and epigenome. The chosen path is that of network optimization techniques, modelled as graphs, allowing the integration of different natures of data. The deployment of clustering and soruce separation methods, incorporating biological a priori (in the line of BRANE Cut and BRANE Clust algorithms) is targeted to the identification of -omics data features driving enzyme production. Attention will be paid to novel evaluation metrics: their standardization remains a crucial stake in bioinformatics.

Offer Requirements

  • REQUIRED LANGUAGES
    ENGLISH: Excellent
    FRENCH: Basic

Skills/Qualifications

Master degree in Data Sciences. Interest and/or experience in signal processing on graphs, source separation ; knowledges in biology and bioinformatics

Map Information

Job Work Location Personal Assistance locations
Work location(s)
1 position(s) available at
IFP Energies nouvelles (former Institut Français du Pétrole – IFP)
France
Rueil-Malmaison
92852
4 avenue de Bois-Préau

EURAXESS offer ID: 311250