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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 7 hours ago
algorithm performance. You will analyze assignment data from December 2025 to the present to identify workload distribution patterns and refine the algorithm using mathematical modeling, programming, and
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. Knowledge of HPC matrix, tensor and graph algorithms. Knowledge on distributed algorithms using MPI and other frameworks such as NCCL. Knowledge of high-performance computing and its applications. Special
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
QCD. The successful candidate will work with Prof. Kostas Orginos on first-principles calculations of hadron structure, including parton distribution functions, generalized parton distributions, and
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in one of the following four topics: 1) quantum algorithms for combinatorial, discrete, continuous, stochastic, robust, or multi-objective optimization; 2) hybrid quantum-classical methods, including
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are seeking a Research Scientist specializing in Machine Learning, Data Science, Data Harmonization, and Synthetic Data Generation to lead the integration, standardization, and privacy-preserving algorithmic
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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research in power electronics, distributed energy resources (DERs), advanced control systems, grid-edge technologies, and system integration. The position requires independent technical leadership in
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productivity. Trains, develops, and empowers staff to effectively perform their jobs. Develops program/departmental communications and may involve promotional materials for distribution. Prepares reports which
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protection of complex, non-transportation interdependent civil infrastructure networks. We seek candidates with particular interests in water distribution systems and networks. Core Responsibilities The
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 22 days ago
regions where ground radar and gauge networks are sparse. In the reverse direction, high-resolution precipitation fields (e.g., MRMS) provide spatially distributed validation for fine-scale soil moisture