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scientific domain and knowledge of high performance and quantum computing and scalable data analytics and/or deep learning Preferred Qualifications: Qualified candidates should have demonstrated management
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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, computer engineering, computer science, or a closely related discipline. Working knowledge of machine learning and deep learning models, including their application within manufacturing environments
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experience of metal additive manufacturing processes Preferred Qualifications: Working knowledge of machine learning and deep learning models, including their application within manufacturing environments
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, computer engineering, computer science, or a closely related discipline. Working knowledge of machine learning and deep learning models, including their application within manufacturing environments
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approaches to optimize the trade-off between privacy and utility especially in the context of large models. Advance knowledge of key AI methods such as deep learning, algorithm design, probability theory
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deep learning models using the Oak Ridge Leadership Computing Facility (OLCF) systems. Conduct research with scalable transformer-based foundation models with large volumes of spatiotemporal physical
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to solve complex problems including information retrieval/extraction, machine learning/deep learning, and networking Special Requirements: Security, Credentialing, and Eligibility Requirements: Export
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such as SCRUM. Strong foundation in machine learning, deep learning, or computer vision Strong Python development skills and familiarity with git, CLI tooling, VS Code Proficiency with PyTorch and/or
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, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow) Experience developing and deploying machine learning or deep learning models Ability to present complex results to multidisciplinary teams, including