31 software-defined-network Postdoctoral positions at Princeton University in United States
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dynamics, and materials chemistry. Strong Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus.Candidates should apply at
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757
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access to state-of-the-art numerical models and high-performance computing systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and
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defined research and laboratory tests and experiments according to prescribed protocols and assigned schedules and developing/documenting new laboratory protocols. All these activities should be done in
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of ecology, evolution, and/or behavior, while also contributing to Princeton University's excellence and diversity, broadly defined. The Program is intended to foster the onward scientific careers
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access to state-of-the-art numerical models and high-performance computing systems at Princeton and in NOAA, working alongside GFDL model developers and software engineers to advance quality assurance and
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expects to have post-doctoral or more senior research positions in Theoretical High-Energy Physics, broadly defined, starting around September 1, 2025. The applicants should have a Ph.D. in Physics and
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of laminar/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH
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models, programming, and quantitative methods. Preferred qualifications include experience in reinforcement learning, neural networks, and/or statistics. Questions can be addressed to Professor Nathaniel
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the Department of Chemical and Biological Engineering to study the biochemical and mechanical mechanisms that define pattern formation during branching morphogenesis of the lung and mammary gland. Further