Context of the position:
Inria is the French national research institute for digital science and technology. The position is part of the Inria Exploratory Action SLIMMEST: Statistical Learning of the Intestinal Microbiota MEtabolism in Space and Time. This project consists in two postdoc positions: one scientist with a systems biology background, and a second with an applied mathematical background. Both scientists will work in close collaboration on an exciting project aiming at building a spatio-temporal numerical model of the gut microbiota. This particular offer concerns the systems biology profile.
The main objective of the SLIMMEST project is to resolve a numerical bottleneck in spatio-temporal modeling of microbiota: the coupling between microbe-scale metabolic models with community-scale dynamics described with PDE models. The recruited person will provide expertise in system biology, microbial metabolism, and community-wide metabolic network modeling. Missions will include modelling and simplification of metabolic models in order to identify metabolic drivers of ecosystems. Such drivers will in turn be used by the second postdoc scientist of the project to develop machine learning techniques and build a partial differential equations (PDE) model of the gut microbiota.
The recruited candidate will be a member of the Pleiade team, a joint research group between Inria and INRAE, in the beautiful city of Bordeaux, France. Pleiade is an interdisciplinary group at the frontier of computer science, mathematics, bioinformatics and biology. One of our main research interests is to develop and validate new computational and numerical models for microbial ecology, that we dedicate to better understand the complex interactions occurring in complex communities of microorganisms known as microbiotas.
Description of the position:
The recruited person will be taken to carry the metabolic-modelling related part of the SLIMMEST project.
The dynamics of a microbial community is driven by the metabolism of its microorganisms, the interactions between those microorganisms, and spatio-temporal interactions between them and the environment. Mathematical and computational models of such dynamics are crucial to build mechanistic hypotheses of the biological observations, as well as predict the evolution of the ecosystems, and actions to lead ecosystems in a desired state. SLIMMEST will combine logic programming and metamodelling of metabolism in a scalable framework applied to communities of the gut microbiota.
The mission of this postdoc position is to develop methods suitable to the reduction of metabolic models for a community. The purpose is to simplify the metabolism of an ecoystem by targeting crucial functions that are main drivers of the ecosystem. The results will be used in mathematical models by the second postdoc scientist of the project.
For that purpose, we must model the metabolism of bacteria from their genome, and connect metabolic networks to the available literature resources on pathways of interest such as short-chain fatty acid production. The simplification of the community metabolism will be performed by modelling constraints and solving combinatorial optimisation problems. In addition, the successful candidate will contextualise the results of community metamodelling back to metabolic networks. The first application of the project will be a model of the murine gut microbiota, with expectations to successfully scale up the size of the community during the project.
2653€ / month (before taxs)
More information and application on: https://jobs.inria.fr/public/classic/fr/offres/2021-03628
Tagged as: Computer Science, Life Sciences
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