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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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to conduct research on developing and using machine learned parameterizations developed from ocean-data assimilation increments. The goal is to develop parameterizations of unresolved processes that will
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, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), bioinformatics, molecular dynamics simulations, and related areas at the interface of computer/data science
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applications at the intersection of statistical mechanics, multiscale simulation, and machine learning. The successful applicant will be appointed through the Chemical and Biological Engineering Department
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their fields of scholarship using techniques from machine learning and statistics. Applicants may also make research advances in the machine learning and statistical methods themselves, as necessary