180 Chemin de Tournefeuille
Location: Toulouse (INRAE Toxalim, 180 chemin de Tournefeuille, 31027 Toulouse, France)
Workplace: TOXALIM Unit (Food toxicology) UMR 1331
Supervision: Fabien JOURDAN (senior researcher INRAE) & Clément FRAINAY (researcher INRAE)
Contract: postdoctoral position, 3 years
Starting date: from April 2020
Grant: France-Germany (ANR-DFG) project MetClassNet.
Principal Investigators on the project: Steffen NEUMANN (IPB, Halle, Germany), Reza Salek (IARC, Lyon, France), Michael WITTING (Helmholtz Zentrum, München, Germany)
OVERVIEW AND STRENGTH OF THE RESEARCH PROGRAM
International grant: This research project is included in an internationally funded grant (ANR-DFG, 928k€) between 4 leading labs in the field of metabolomics in France and Germany. Funding includes travel grants (possibility to stay few weeks in the different labs), functioning and publishing costs.
Multidisciplinary research: the proposed research project is fully computational but the postdoc will work closely with chemists and biologists. Application fields will also be broad from model organism (C. Elegans), plants to human.
Work in a friendly computational biology group: The Toxalim team gathers 9 bioinformatics scientists with various skills (modelling, machine learning, web programming, graph algorithms…). Together with a strong network in France and beyond the team develop original methods and tools (e.g. MetExplore web server). Importantly we aim at maintaining a friendly and supportive work environment (social events, hackathons). Details on the group can be found here:
Starting date: sooner is April 1st 2020 but it is still flexible
Overall objective: integrate networks in metabolomics. Metabolism is a key system in any living organism and its understanding can help in tackling many health and environmental issues. In this context, metabolomics is a cornerstone method to produce observational data on metabolism. Nevertheless, this approach still faces several challenges among which: improving metabolite annotation, biochemical reaction description and data interpretation. Network science is playing a major role in this context. But currently networks are of various sources (experimental or knowledge based) and it is necessary to integrate them in order to go further in our understanding of metabolism.
Creating a computational system for network integration. The first aim will be to create a modular and flexible computational system to integrate the networks. Beyond data storage, information visualization and query engine, the system should support programmatic graph navigation and operation in order to integrate higher level information extraction technics based on graph algorithm.
Developing new algorithms based on knowledge and experimental networks congruency. Using the newly created framework, the aim will be to propose new graph-based algorithms to exploit the topology in order to 1) assist in metabolite annotation 2) perform gap filling in metabolic networks 3) help in metabolomics data interpretation. Algorithms will be used on data produced within the consortium and beyond. It will be possible, thanks to our collaborators, to produce new data to validate the hypothesis raised by the algorithms.
Applicants should have the following skills:
• PhD in computer science/bioinformatics required
• Good communication skills required
• Network science required
• Network oriented databases (e.g. Neo4J) ++
• Versionning, continuous integration ++
Applicants will have to be computer scientist happy to work in a multidisciplinary project and environments. Biology or chemistry background is not mandatory but it will be necessary to be eager to learn and exchange with researchers in these fields.
HOW TO APPLY
Please send the following information to Fabien.Jourdan@inrae and Clement.Frainay@inrae
• Cover letter summarizing your expertise and past experiences
• Contact information for 3 references that can discuss your expertise