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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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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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