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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 271598471 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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of artificial intelligence on society, as well as broader questions surrounding the application of statistics and machine learning in social science. The position requires no teaching, though some mild
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on projects related to machine-learning for mass spectrometry-based metabolomics data. Positions are available starting July 2024, and will remain open until excellent fits are found. Successful candidates will
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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senior ranks may have multi-year appointments. A PhD is required, with appropriate research experience in quantitative biology, (bio)physics, (bio)engineering or related Engineering and Physical sciences
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. Qualifications: Successful candidate will have a Ph.D. in Philosophy, Religion, or a related field and must have less than three years of post-PhD research experience prior to anticipated start date. Applicants
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emerging technologies such as artificial intelligence, quantum technologies, and space-based systems, including large satellite constellations. A recent PhD in physics, engineering, computer
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theoretical computer science and theoretical machine learning. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory