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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
) ecosystem a cloud-based platform that provides secure access to biomedical data, analytic tools, and collaborative workspaces. This position offers the opportunity to work on cutting-edge initiatives aimed
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research and innovation at the heart of its educational project as a driving force of a business model. In its research approach, the UM6P promotes transdisciplinary thinking, an entrepreneurial spirit, and
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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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can focus on learning for planning, risk-aware motion planning under uncertainty, learning of interaction models, multi-robot learning, multi-modal prediction models, or other related topics
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. Your overall focus will be to help develop a semantically integrated data ecosystem that links experimental data across our pilot plant and coatings science center using ontologies and knowledge graphs
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the Western United States. The candidate will contribute to innovative research quantifying the risk of losing key forest ecosystem services (e.g., timber production, carbon storage, recreation, soil erosion
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flux measurements using biogeochemical modeling. They will be responsible for managing projects related to field instrumentation and ecosystem flux modeling. 20% designing and implementing trace gas flux
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monitoring and modeling across various freshwater systems. Compile and critically review the current state of knowledge on N2O emissions and modeling in freshwater ecosystems. Acquire, organize, and analyze
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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of biological questions and experimental systems – from ecosystems to microbiology and developmental biology, from evolution to cell biology, from molecular biology to systems biology, bioinformatics, and