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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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on the creation and application of predictive simulation models Collaboration on the development of data processing and fusion algorithms Collaboration on the virtual modeling of marine structures Conducting and
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning
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for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems
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development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
applicability to the design, development, and science return of space science missions. There is growing interest for the tools and practices of uncertainty quantification to be used to inform the engineering
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, lead large-scale benchmarking across the full stack, and develop scalable classical simulations (e.g., tensor networks)—including performance bounds beyond brute-force classical simulability. This role