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- Interfacing machine learning with climate models Company: Princeton University Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid
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- Interfacing machine learning with climate models Company: Princeton University Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid
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conduct research on the use of machine learning in ocean climate models. The goal is to demonstrate the successful use of machine learned parameterizations of unresolved processes that will reduce biases in
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approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a range of exciting projects
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conduct research on developing and using machine learned parameterizations for mixing in the ocean surface boundary layer. Our previous work has demonstrated the utility of using neural networks to improve
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conduct research on developing and using machine learned parameterizations for mixing in the ocean surface boundary layer. Our previous work has demonstrated the utility of using neural networks to improve
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, biogeochemical models, and machine learning. The ideal candidate will have a background in ocean modeling, but candidates with the necessary background in ocean biogeochemistry and/or geophysical fluid dynamics
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access to PLI's $9.6M GPU cluster (300 H100s), among the largest machine learning computer cluster in academia. In addition, PLI seed grants enable advances in AI-related research in the humanities, social
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Qualifications: - Previous experience in data management and data analysis using a variety of statistical and/or machine learning methods - Application of statistical/deep learning tools to answer biology related
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and excellent communication skills are also essential. Preferred Qualifications: - Previous experience in data management and data analysis using a variety of statistical and/or machine learning methods