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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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Requisition Id 15591 Overview: We’re hiring a Team Lead, Research Computing Operations (RCO) who will guide a high-impact team dedicated to supporting ORNL’s research community through expert
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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
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). Knowledge of high-performance computing or cloud environments for large-scale data. Strong collaboration skills and ability to work in interdisciplinary teams. Special Requirements: Applicants cannot have
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, control theory, data science, data driven methods, discrete mathematics, graph algorithms, high-performance computing, integral equations and nonlocal models, linear and multilinear algebra, machine
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experience in hydrological or Earth system modeling, with emphasis on process understanding and prediction. Strong background in computational sciences, including numerical methods, high-performance computing
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across ORNL’s high-performance computing (HPC) environment, supporting scalable, reliable, and secure computing and storage capabilities. Applications are reviewed on an ongoing basis as new positions
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through the High Flux Isotope Reactor, the Radiochemical Engineering Development Center, ORNL’s other nuclear facilities, and an assemblage of world-leading scientists and engineers. Please visit https
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that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing; The design of architectures
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for the design and analysis of computational methods that accelerate data analytics and machine learning, especially as the apply to scalable high-performance computing, cloud computing, and large interconnected