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Référence : UMR6074-ANNSIE-001
Lieu de travail : RENNES
Date de publication : vendredi 28 septembre 2018
Type de contrat : CDD Scientifique
Durée du contrat : 6 mois
Date d'embauche prévue : 1 décembre 2018
Quotité de travail : Temps complet
Rémunération : entre 2530€ et 2919€ bruts mensuels selon expérience
Niveau d'études souhaité : Doctorat
Expérience souhaitée : Indifférent
The IDEALG project aims at better understanding the characteristics of macro-algae, notably brown algae, to promote this valuable resource. Lately, several studies shed light on the essential role of bacteria living on the alga and in its environment. They can promote the normal growth of the alga and acclimation to salinity (Dittami et al., 2014; Tapia et al., 2016; Dittami et al., 2016). A research team in Roscoff Biological Station is specialized in algal metabolism and sequenced Ectocarpus's microbiota in various growth conditions. The objective of this research project is to develop methods for exploiting this data in order to identify families of interesting bacteria with respect to the algal growth.
The Dyliss team developed methods based on combinatorial optimisation to facilitate the prediction of cooperation between hosts and their microbiota when knowledge for the organisms is limited (genomic information) (Frioux et al, 2018). These approaches enable to restrain the search space and identify communities of bacteria that are likely to interact positively with the host. The objective of the recruited research will be to explore and reduce this search space with additional criteria taking into account the competition events that can happen in bacteria communities. The automatized selection of bacterial communities with these new criteria will be modelled as a new combinatorial problem (Gebser et al., 2012), preference problem (Brewka et al., 2015), or temporal problem (Cabalar et al., 2018).
Fom the application point of view, the project aims at using these methods to study the dependencies of Ectocarpus subulatus towards its microbiota in various conditions of antibiotics and salinity, and therefore better understanding the physiology of this brown alga. The objective is to identify bacteria of interest and their key functions in each condition.
- The candidate must have a Phd degree in computer science, bioinformatics or biology.
- Skills in constrain-based programming (combinatorial or MILP optimization).
- Skills (possibly to be developed internally to the team) in omics-data analysis.
- Programming : python.
Contexte de travail
The Dyliss team is a bioinformatics team of the computer science laboratory of the university of Rennes. It is supported by CNRS, Inria and University. The research program will be handled in the context of the IDEALG research program, a long term biotechnology program focused on the understanding of macro-algae (Plan d'Investissement d'avenir, 2012-2020).
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