The rumen microbiota is a galaxy of microbes forming a highly evolved microbial digestive system. This project aims at developing mathematical models for predicting rumen function with the interest of providing tools that help the design of nutritional strategies for improving animal feed efficiency and for reducing ruminant environmental footprint (e.g. methane emissions). The postdoc fellow will be part of the European H2020 project MASTER – Microbiome Applications for Sustainable food systems through Technologies and EnteRprise.
By combining computational biology tools [1], macroscopic fermentation models [2–4] and microbial time series [5], we aim at filling the current gap between the available omics data of the rumen microbiome and the existing models of rumen function [6]. Mathematical models will be constructed using experimental data of in vitro and in vivo studies from our rumen microbiology MASTER partners.
The research will be carried out at the MoSAR (systemic modelling applied to ruminants) team from the French National Institute for Agicultural and Environmental Research (Inrae) in Paris. The postdoc fellow will work with Rafael Muñoz-Tamayo and collaborate with Chris Creevey and Francesco Rubino from the Creevey lab.
Background and skills required
• PhD in applied mathematics or computational biology.
• Knowledge on dynamic modelling of biological systems. Expertise in dedicated software: R, Scilab/Matlab. Experience on analysis of microbial omic data is a plus.
• Excellent communications skills, willing to discuss with scientists with different backgrounds.
To postulate, send your motivation letter, CV and the name of two scientists (references) to
[email protected] References
1 Wilkinson, T. J. et al. Front. Microbiol. 9, 1095 (2018)
2 Muñoz-Tamayo, R. et al. Anim. Feed Sci. Technol. 220, 1–21 (2016)
3 Muñoz-Tamayo, R. et al. Animal 13, 1180–1187 (2019)
4 Munoz-Tamayo, R. et al. PLoS One 14, e0226243 (2019)
5 Bucci, V. et al. Genome Biol. 17, 1–17 (2016)
6 Huws, S. A. et al. Front. Microbiol. 9, 2161 (2018)
