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skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
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researcher will be responsible for conducting ethnographic research on the Morbras and Bièvre rivers. He or she will be selected for their knowledge of water, their mastery of cartographic tools (GIS) and
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biostatistics and handling heterogeneous datasets (R or Python; GIS experience appreciated); • Solid knowledge of fire ecology, soil functioning, and/or biogeochemical cycles; • Strong interest in
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Bioinformatics expertise of Dr. Raimondi on the development of GI NN methods and their application to relevant biological problems with the expertise of Dr. Bry and Dr. Trottier on the statistical inference
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monitoring using SAR and multi-spectral images, GIS, scientific programming - English proficiency, team work, reporting, redaction of scientific publication, organization and project management
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FieldEnvironmental scienceYears of Research ExperienceNone Additional Information Eligibility criteria PhD Thesis in population ecology Skills in data analysis, GIS data and database management Skills in writing
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hydrology and social geography. Proficient in geographic information systems (GIS) and spatial data analysis. Experience in workshops organisation Good French speaking and reading capacities and good English
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Heudiasyc laboratory (UMR CNRS 7253), computer engineering department (GI), as part of the ANR Succen project. Your responsibilities · Conduct energy measurement campaigns · Develop a smartphone application
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on spatial remote sensing and geographic information systems (GIS). The new mathematical models developed as part of the Math-Vive PEPR will serve as a basis for building predictive analysis models and
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potentiation triggered by the activation of Gi/o protein-coupled receptors (like GABAb and µ opioid ones) that are unique for the central nervous system. Activation of these receptors on MHb axonal terminals