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pivotal role in advancing scientific discovery by working on state-of-the-art deep learning methods and apply them to scientific domains. There will be an opportunity to work with multidisciplinary
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. Solid background in machine learning techniques and practical experience in computer vision applications. Proficient programming skills and experience in one or more deep learning tools. Proven track
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scientific and security problems of interest to Brookhaven Lab and the Department of Energy (DOE). Topics of particular interest include novel development of deep learning ML models and adaptation of existing
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experience in deep learning algorithms for object detection/classification/tracking and/or natural language processing Track record of producing high-quality software on schedule Experience working in
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on diverse scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) novel development of deep learning ML models and adaptation
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collaborators working on diverse scientific and security problems of interest to Brookhaven Lab and the Department of Energy (DOE). Topics of particular interest include novel development of deep learning ML
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of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) novel development of deep learning ML models and adaptation of existing ones for scientific and security
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, particularly with a focus on aerosol-cloud-precipitation interactions. The ideal candidate will have a strong interest on the study of processes that impact the lifecycle of deep convective clouds using high