Postdoc position: Data management and data mining for trade-off predictions in plant biology
CDD · Postdoc · 36 mois Bac+8 / Doctorat, Grandes Écoles INRAE - UMR 1332 Biologie du Fruit et Pathologie · Villenave d'Ornon (France) 31k€ yearly before-tax salary (approx. 25k€ net)
Date de prise de poste : 1 décembre 2022
data mining machine-learning open science data-steward trade-off
A 36 months’ position supported by Bordeaux Plant Science (BPS) research program is available in the BFP research unit in Bordeaux, France (https://www6.bordeaux-aquitaine.inrae.fr/bfp_eng/). This post-doc position is one of 19 offered positions as part of Bordeaux University excellence BPS program, which will provide access to many scientific events and resources.
The ambition of the Bordeaux Plant Science (BPS) project is to better understand and master the mechanisms involved in the trade-offs between biomass production, resistance of plants to biotic and/or abiotic stress and the quality of plant products. This project has three main objectives: identify molecular, metabolic and physiological mechanisms that control the performance of trade-offs in plants; study the (epi)genetic and environmental determinism of plant performance trade-offs; control the functioning of the plant, its culture and its products, especially in relation to societal demands and environmental disturbances.
The Meta Team is leading the BPS project, and this postdoc will be part of WP12, which is also lead by the Meta Team. This WP aims to deal with all data-related questions in the project, including the collection of FAIR data using an in-house system, data-mining of multi-level datasets, and prediction of plant performance and trade-offs based on the data generated in this project.
Job description: The post-doctoral fellow will be responsible for the collection of FAIR data and metadata in the different laboratories involved in the project and to store them using an in-house tool. He/She will also have to identify or define different trade-offs in the plant development with regard to traits such as yield, quality, or stress resistance. He/She will be involved in the collection and metabolomic analysis of samples that will be performed by the Bordeaux Metabolome Platform.
The post-doctoral fellow will also be responsible for developing models capable of predicting trade-offs from the phenotypic and omics datasets that will be collected in the project, by using state of the art machine-learning methods.
The post-doctoral fellow will join a modeling group within the Meta team, in which several researchers, other post-doctoral fellows and PhD students participate.
Environment: The position is open at UMR BFP, a partnership between INRAE (Divisions of Biology and Plant Breeding and Plant Health and Environment) and the University of Bordeaux. It constitutes a major pillar of plant biology research in Nouvelle-Aquitaine. We are located on the plant science campus of the INRAE (French National Research Institute for Agriculture, Food and Environment).
The Meta team is a multidisciplinary team (analytical chemistry, biochemistry, molecular biology, physiology, statistics and bioinformatics) using Systems Biology approaches to understand metabolism and the way it participates in the performance of plants, whether in terms of yield or adaptation to abiotic and biotic stress. The Meta team also hosts the Bordeaux Metabolome Platform that enables a wide range of targeted and untargeted metabolomics.
Bordeaux is an easy-going and enjoyable UNESCO world heritage city with many cultural, social, sportive events, famous for its vineyards and only one hour away from marvellous sand beaches.
Skills: The candidate must be aware and interested by FAIR data and machine learning. Some knowledge in plant physiology, metabolomics and/or plant metabolism would also be appreciated. The candidate must have strong relationship skills, be able to work in a network and to report on his/her results (oral and written communications).
Procédure : The candidate will submit their application, consisting of a letter of motivation and a CV (including list of publications, if applicable), to Sylvain Prigent (sylvain.prigent[à]inrae.fr) and Yves Gibon (yves.gibon[à]inrae.fr).
Date limite : 31 octobre 2022
Offre publiée le 21 septembre 2022, affichage jusqu'au 31 octobre 2022