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Field
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NSF funded projects, advancing the knowledge about distributed systems, developing novel algorithms for distributed resource and workload management, simulating and emulating systems, as
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Software-Defined Networking (SDN) solutions to dynamically manage network congestion and improve communication efficiency. Research and develop topology-aware collective communication algorithms to optimize
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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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using jets and heavy-flavor probes. The candidate will also participate in algorithm and software development for the LHCb trigger system as part of the Real Time Analysis Project. A Ph.D. in experimental
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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Requisition Id 14997 Overview: We are seeking a postdoctoral fellow to help develop world-class capabilities related to manufacturing science and technology associated with the Oak Ridge National
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magnetic resonance imaging using pulse sequence design, image reconstruction, and real-time image processing, for brain, body, and fetal applications. Responsibilities: The successful candidates will develop
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mathematics. Develop and implement machine learning algorithms, with a focus on reinforcement learning, to solve challenging mathematical problems. Collaborate with other team members to advance the research
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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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the following objectives: 1. Characterize 3-D Urban Structure and Change: Utilize data from multiple remote-sensing platforms and deep learning algorithms to generate high-resolution maps of 3-D urban structure