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University to merge CFPS data with granular COVID mitigation policy data and specify models for evaluation of policy effects. *Communicate with the director of the secure data enclave at Peking
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to ion beams with well-controlled energies and incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes
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/or energy *Strong methodological and quantitative skills, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling
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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