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. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized
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foundational ML and NLP innovations. This work involves the development and applications of encoding and generative NLP models (e.g., large language models, LLMs), and includes model training, tuning and
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to provide electro-mechanical drafting, document revision control, and library creation/management, using a variety of CAD/CAM platforms. Tasking will also include provision of drafting support for development
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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 of existing ones
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push the envelope to accomplish our missions, we develop novel tools and techniques in biochemistry, molecular genetics, structural biology, cell biology, plant pathology and bioimaging that also benefit
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programs on trigger/data acquisition, high-performance computing, and silicon detectors. The group also contributes to the development and construction of the LBNF/DUNE detector in collaboration with the EDG
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administrative support. Essential Duties and Responsibilities: Provide overall leadership and direction of BNL’s occupational medicine program, including program development, administration, creation and
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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) development of novel machine learning models and adaptation
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these applications to inform new foundational ML and NLP innovations. This work involves the development and applications of encoding and generative NLP models (e.g. large language models, LLMs), and includes model
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for development and special project initiatives. Essential Duties and Responsibilities: CAD library creation/management Create and maintain Schematic and PCB Symbols per IPC-2221 Experience with ECN