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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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) on the development of advanced Pediatric MR research with a primary focus on the brain and/or heart (e.g., MR spectroscopic imaging, MR elastography, susceptibility mapping and/or dynamic imaging). The candidate will
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and to develop novel and improved platforms for quantum computation and communication and thus strengthen U.S. leadership in QIST. This calls for expertise across disciplinary sciences – encompassing
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing
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University, to begin as early as July 1, 2025. Topics include the experimental quantum simulation of chemical and condensed-matter systems using 1D and 2D ion arrays, and the development and optimization
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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. The mission is to address challenges facing scalable quantum computing and to develop novel and improved platforms for quantum computation and communication and thus strengthen U.S. leadership in QIST
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partners in the digital health and health delivery ecosystem. Research Responsibilities Responsibilities will vary depending on the Fellow’s background, but may include: • Developing machine learning
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to support a two-year Small Business Technology Transfer project (STTR) funded by the National Science Foundation. The successful candidate is expected to support the development, simulation and