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well as with other national laboratories, academia, and industry, to investigate the fast-moving and dynamic computing landscape. Major Duties/Responsibilities: Work with project teams to create, evaluate, and
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manufacturing datasets, including sensor streams, in-process signals, post-process characterization data, simulation outputs, and digital twin data. Develop, integrate, and evaluate AI/ML models for anomaly
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research assignments related to advanced thermal and energy system technologies, including: Conduct experimental and analytical research to evaluate advanced thermal and energy technologies, including energy
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Gaussian-process emulators for accelerating parameter estimation and uncertainty propagation Selective cross-scale evaluation using complementary ecosystem observations (e.g., experiments) to test how AI
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into experimental design, data analysis, and detector performance evaluation workflows Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating
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single node between multiple secure workloads. Investigate and evaluate mechanisms for secure encrypted communication across RDMA based networks. Design and evaluate key distribution and management
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. Design and evaluation of ephemeral, user-configurable, and composable data and storage systems. Design system-level approaches for time-sensitive or data-intensive processing of data originating