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, New York 14850, United States of America [map ] Subject Areas: Data Science / Statistics , Applied Mathematics , Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning
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in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
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to transform millions of plug-in electric vehicles (EVs) into a vast, distributed network of mobile batteries that actively support the power grid to facilitate the deep integration of intermittent renewable
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to develop and deploy advanced AI-driven learning, prediction, and decision-making tools to transform millions of plug-in electric vehicles (EVs) into a vast, distributed network of mobile batteries