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: 277393135 Position: 2025 Postdoctoral Research Associate - AI/machine learning for analytical and forensic chemistry Description: The Skinnider Lab at Princeton University aims to recruit a postdoctoral
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 277494287 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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] Subject Areas: Machine Learning / Machine Learning Analytical Chemistry / Current Advances in Chemistry & Biochemistry Computational Science and Engineering / Machine Learning Artificial Intelligence
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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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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biology-experimental and/or theoretical biophysics-experimental and/or computational genomics-computer science, statistics, and/or machine learning with applications relevant to genomics-bioinformatics
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, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational
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: 278255392 Position: Postdoctoral Research Associate in Microfluidics, Nanofabrication, and Nanophotonics Description: The Department of Electrical and Computer Engineering has opening for postdoctoral
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: 277839347 Position: Postdoctoral Research Associate Description: Postdoctoral Research Associate and Associate Research Scholar PositionsPrinceton Precision HealthPrinceton UniversityThe mission
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials