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teams to codesign hardware, algorithms, benchmarks and software for QHPC systems, aiming to advance our strategic goals in leveraging quantum computing and high-performance computing (HPC) to develop
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and numerical algorithms for modeling and simulation of nuclear systems. Computational Nuclear Engineers within the RTHPCM group will work with group, section, and division members and external
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and numerical algorithms for modeling and simulation of nuclear systems. Computational Nuclear Engineers within the RTHPCM group will work with group, section, and division members and external
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-class S&T products for sensitive national security missions. The selected candidate will support research efforts in signal processing and analysis, with an emphasis on the development of novel algorithms
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Qualifications: PhD and 2+ years of experience in a computational discipline such as Computer Science, Statistics, Biomedical Engineering, or a related field. Experience with multi-modal learning across modalities
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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-flows. Basic Qualifications: PhD in mathematics, computer science, engineering, or related field earned within the last 5 years. Preferred Qualifications: Experience with mesh generation/CFD applications
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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class research capabilities focused on solving the world’s most challenging problems through artificial intelligence and data driven algorithms and systems. CSMD creates the mathematics, artificial
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a