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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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, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models
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epilepsy patients and non-human primates are conducted using identical behavioral paradigms and combined with computational approaches. We are seeking an extremely motivated postdoctoral researcher with
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, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models
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of epistemic values in scientific practice, or the expression of values in collective behaviors (e.g., in online social networks). The proposed research is expected to yield both theoretical and empirical
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of epistemic values in scientific practice, or the expression of values in collective behaviors (e.g., in online social networks). The proposed research is expected to yield both theoretical and empirical
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
The Atmospheric and Oceanic Sciences Program at Princeton University, in association with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), seeks a postdoctoral or more senior research scientist
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behavioral paradigms and combined with computational approaches. We are seeking an extremely motivated postdoctoral researcher with background in human or monkey electrophysiology. Studies will include
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computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and
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values in collective behaviors (e.g., in online social networks). The proposed research is expected to yield both theoretical and empirical publications. The candidate will be appointed in the Department