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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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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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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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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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Eligibility criteria * Fieldwork in North African context; knowledge of Arabic would be appreciated * Organization of scientific events (e.g., study days) * Scientific writing * GIS skills * Photography skills
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Additional Information Eligibility criteria Technical skills: proficiency at ecological modelling, use of the Unix/Linux environment, proficiency at oceanographic data repositories and GIS tools, good
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candidate will join an interdisciplinary research team hosted by the CRESAT laboratory, composed of the Principal Investigator (PI), a project manager, a GIS specialist, three postdoctoral researchers, and
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Investigator (PI), a project manager, a GIS specialist, three postdoctoral researchers, and several research assistants. In a context marked by renewed global interest in nuclear power and intensifying debates
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candidate will join an interdisciplinary research team hosted by the CRESAT laboratory, composed of the Principal Investigator (PI), a project manager, a GIS specialist, three postdoctoral researchers, and
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in ecological fieldwork, ideally in wet grassland or agricultural systems - Skills in GIS, remote sensing, and spatial data analysis (bonus: agent-based modelling) - Demonstrated ability to work in