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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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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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-to-Decadal Variability & Predictability Division, Technical Services and Modeling Systems Division. The selected candidate will have access to state-of-the-art numerical models and high-performance computing
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Improving Ocean Surface Boundary Layer Mixing Parameterizations with Langmuir Turbulence and Machine Learning The Atmospheric and Oceanic Sciences Program at Princeton University, in association
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health services to Princeton University faculty, staff, and employees. An integrated, evidence-informed model guides all UHS practices and services. UHS leverages clinical encounters and prevention efforts
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methodologies for modeling and analyzing spatially embedded networks. This project aims to advance the understanding of infrastructure systems by leveraging spatial networks to capture complex interdependencies
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research thrusts (or both): 1.Applied operations research: scholars will develop and implement novel methods to improve the computational performance and resolution of large-scale optimization models
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quantitative intravital microscopy. 2) Computational or Cell biologists (with expertise in quantitative microscopy, statistical modeling, cell culture, and/or biochemistry) looking to develop expertise in
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the School of Architecture and Associated Faculty of the Department of Computer Science. The desired start date is Spring 2025. Appointments are for one year with the possibility of renewal pending
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, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling *An interest in mixed-methods approaches, including also