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position will contribute to the Forge project, which is focused on developing advanced multimodal AI capabilities that can learn across distributed data environments without requiring sensitive data to
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computing, including distributed computing, high-performance computing (HPC), or machine learning (ML) Interest in Standard Model measurements and/or searches for new phenomena Application Review Review of
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these fforts. A successful candidate will collaborate with scientists in DIS, Environmental Sciences division and Argonne leadership Computing Facility to further develop the AI foundation models
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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guide synthesis in real time AI-enabled analysis of high-throughput, multimodal experimental data with uncertainty quantification Integration of edge computing, high-performance computing (HPC), and
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The Computing, Environment, and Life Sciences (CELS) Directorate seeks an outstanding scientist to lead and support frontier research at the intersection of AI, autonomous platforms, data
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operational optimization. Familiarity with distributed control architectures, industrial networking, motion control, and high-availability environments. Experience supervising or mentoring scientific
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Directed Research and Development (LDRD) project. This research focuses on understanding how critical elements are distributed at mineral-water interfaces, with the goal of revealing the fundamental
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The Computing, Environment, and Life Sciences (CELS) Directorate seeks an outstanding scientist to lead and support frontier research at the intersection of AI, autonomous platforms, data
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accelerator physics, beam dynamics, or free-electron-laser science. Experience with machine learning, surrogate modeling, optimization, or AI-enabled scientific computing. Experience working with complex