Improving the efficiency of animals in the livestock sector is a prioritized research topic for contributing to competitive industries under the Horizon 2020 strategy. Progress must be made in identifying appropriate phenotypes and appropriate indicator traits that reflect improved resource-use efficiency. In the framework of the Feed-a-Gene EU project(www.feed-a-gene.eu; Grant Agreement n°633531), we will explore and identify new animal traits directly or indirectly related to individual variation in the animal’s feed efficiency under different environmental conditions. We have already acquired many transcriptomics data in different tissues from pig lines divergently selected for feed efficiency and reared under different conditions.
Description of the job
The post-doctoral fellow will have 1/ to create a dedicated database to merge and organize the various molecular data of different experiments, and 2/ to meta-analyze the data in order to put evidence on the main coherencies (at individual genes and(or) pathway levels). He/She will use bioinformatics (assembly of data, data-mining, gene networks) and statistical techniques (meta-analysis, factor mining analysis) to determine relevant indicators of feed efficiency.
The work will be carried out at INRA (National Institute for Agricultural Research), in a research unit (UMR1348 INRA/AgroCampus-Ouest, https://www6.rennes.inra.fr/pegase) located in Rennes/Saint-Gilles (France). This unit gathers over 150 persons studying animal physiology and animal production systems. The post-doctoral fellow will work with scientists from the team entitled “Physiology and Metabolisms of Growth” having great expertise in tissue energy metabolism including omics.
To be considered, the successful candidate must have a PhD related to biological or bioinformatics sciences. Pre-doctoral candidates expecting to defend their thesis before the end of the year can also apply. A prior experience in the analysis of high-throughput tanscriptomics data is strongly recommended. Skills in French will be appreciated but is not mandatory. Funding is available for 1 year (January 2016-december 2016). Gross salary is 27600 euros (2300 euros/month).
Please send your application by October 30th 2015 by e-mail as a single PDF (CV + cover letter summarizing research and career goals + 2 references) to Florence Gondret (
) and Isabelle Louveau (