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Field
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are looking for a postdoctoral researcher with a strong scientific drive to contribute to the international research front on forest resilience in a changing climate. The project offers a unique opportunity to
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responsibility. Through project collaborators, the candidate will have the opportunity to develop a broader international network around ocean observations, modelling, climate variability and dynamics. Salary and
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tools, including 4D point cloud modeling and state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier
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associate will lead collaborative efforts in advancing research focusing on the intersection of infrastructure, climate, and human health. Examples of current active projects include: Developing optimization
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academic and industrial domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape
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, such as sedimentation, meltwater flow, and vegetation change, into active drivers of adaptive design. This interdisciplinary work combines advanced computational tools, including 4D point cloud modeling and
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(Sutton Bonington Campus, University of Nottingham, UK). This research is part of a trilateral grant in Climate Proofing Agriculture, involving partners in the USA (Eric Lam’s group Rutgers) and Germany
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the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor master students and PhDs Education, qualifications, and experience Applicants must have an earned doctorate in Agronomy
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environment thanks to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. About
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. Investigate the interactions between soil microbes and their environment using field and laboratory experiments. Analyze data on soil microbiomes, nutrient cycling, and soil biological processes. Develop models