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, enhanced sampling, QM/MM) Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation
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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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system integration, as well as embedded controller development. Experience in modeling converter topologies and distribution grids, developing control algorithms, and implementing controller code is
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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance
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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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will focus on the design and implementation of photogrammetry and 3D computer vision algorithms to support high-volume and high-throughput scientific data applications, primarily with remote sensing
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power electronics resources modeling, explore different intelligence algorithms to enhance ease of usage of simulations, and different applications of EMT simulations. Selection will be based
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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Requisition Id 15854 Overview: We are seeking a research professional with fundamental knowledge in artificial intelligence (AI) who will focus on developing and applying AI algorithms to signal