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supporting new research and engineering using ORNL’s Frontier exascale supercomputer for its dense GPU-based HPC resources to train, deploy models and create large-scale production datasets for high-impact
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and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures
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extreme scenarios. Your tasks: Conduct security and resilience studies for highly stressed systems (e.g., multiple faults, high renewable shares, or equipment failures). Evaluate system vulnerabilities and
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or engineering comparable with exception for a lesser degree with significant related professional experience • Proficient in Kubernetes and related technologies with multiple years of experience • Experience with
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in high-performance computing systems, storage and I/O. Extensive knowledge on parallel file systems, GPUs, and their trends. (more than 3 years of working with these systems) Experience with
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of and logging from many system components (video acquisition, animal tracking and pose estimation, microscopy image acquisition and/or physiological recordings, video game engines, multiple displays, etc
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The ability to develop the business model for sustainable leadership-class computing and manage a complex budget comprising multiple funding sources and time horizons and comprising capital and operating
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conducted in collaboration with NVIDIA, leveraging state-of-the-art GPU-based simulation environments and AI platforms. The position will be hosted within the Medical Imaging and Robotics group led by Dr
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) invites applications from outstanding candidates for multiple faculty positions. The recruitment process will prioritize candidates applying for the Assistant Professor position. However, exceptionally
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acquisition and/or physiological recordings, video game engines, multiple displays, etc.) as well as development of geometrically precise, reconfigurable, closed-loop virtual social paradigms that can be