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Connallon): Meta-analysis and modelling of why additive genetic variance for fitness is so high, and what it means for adaptation and population viability (no prior modelling experience needed). (Lab: https
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of the CEFE in community ecology and species distribution models with that of IMAG in probability, statistical learning, and model validation. This project falls within the scope of statistical artificial
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). Expertise in quantitative statistical analysis and ecological modelling. Experience in analyzing biodiversity patterns and land-use change impacts on plant communities. Advanced experience in programming
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increasingly understand that species interactions mediate the impacts of externalextenral stress on biodiversity, three substantial challenges exist for translating the potential of ecological modelling
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ASE is a diverse school focusing on the connections between geosciences, ecology, society and Earth systems. Our approach integrates these disciplines to examine big environmental challenges both in
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The candidate will hold a PhD. in oceanography or marine ecology and have significant experience in 3D modeling, ideally at the interface between physical and LTL (biogeochemical) models, between physical and HTL
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ASE is a diverse school focusing on the connections between geosciences, ecology, society and Earth systems. Our approach integrates these disciplines to examine big environmental challenges both in
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project deadlines the ability to work independently and in a team self-motivated and responsible Preferred modeling skills: GCAM, Environmental Input-Output Analysis, Industrial Ecology Models. What We
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group led by Dr. David Klinges in the Department of Ecology, Evolution & Natural Resources. Our work combines computational modeling, field studies, and laboratory experiments to understand how
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profile in Ecology. Specific Requirements Experience in freshwater ecology and biodiversity, in particular on metacommunities of temporary rivers. Experience in metacommunity modelling. Knowledge on river