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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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Develop a prototype neural network model for modeling strongly correlated materials. Implement and experiment with models using PyTorch and TensorFlow frameworks. Collaborate with team members to evaluate
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will be part of a team that already uses machine learning to improve online accelerator models and that develops correction algorithms for accelerator operations. This position is for a 2-year research
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scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) Large scale foundation model for science and engineering; (ii) Causal
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on the challenges presented by analyzing, interpreting, and using data at extreme scales and in real-time. The data science program is accompanied by significant computational modeling research efforts supporting
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scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) Large Language Model (LLM) and Reasoning Language Model (RLM) for science and
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. Experience creating and checking detailed mechanical drawings and 3D models of pipe systems and components andmanaging the work of mechanical designers. Experience with creating and reviewing detailed piping
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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 and application of machine learning models, especially
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, neutron source, or other major scientific facility. Experience in developing and deploying AI models. Demonstrated ability to collaborate on distributed software development teams. Experience with HTTP APIs
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Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a wide range of material parameters. The CFN develops and utilizes