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implement project requirements in developed system architectures and software. Interdisciplinary Collaboration: collaborating with a highly diverse and multidisciplinary team – from photogrammetrists
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, especially for GPUs across multiple hardware vendors, as well as experience in software sustainability and design patterns is expected. Major Duties/Responsibilities: Collaborate within a multi-disciplinary
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offered a salary at or near the top of the range for a position. Link to benefits. https://jobs.ornl.gov/content/Benefits/?locale=en_US Overview: We are seeking a Machine Learning Research Scientist who
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to the development of scalable and efficient implementations of these algorithms for state-of-the-art high performance computing facilities. Collaborate within a multi-disciplinary research environment consisting
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and
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control regulations and Department of Energy (DOE) directives. The successful candidate will help enable international collaboration while protecting national security and advancing ORNL's scientific
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high-performing multidisciplinary team covering, HPC/data infrastructure, data engineering, platform engineering, user engagement, and operations. Foster a culture of excellence, collaboration, inclusion
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of AI for science such as: scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You’ll help design, train
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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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Requisition Id 16723 Overview: We are seeking a Postdoctoral Research Associate with expertise in artificial intelligence (AI) and machine learning (ML) for multiscale physical systems