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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 1 hour ago
@orau.org Qualifications Background in engineering, computer science, or a similar field. Background in software tools such as Matlab, Python, and C/C++ Experience developing machine learning algorithms
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on developing and analyzing algorithms, building reproducible computational studies, and disseminating results in leading venues. The position collaborates with faculty, students, and external partners
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: Computational Sciences / Bio-computing Appl Deadline: (posted 2025/11/10, listed until 2025/11/30) Position Description: Apply Position Description As a computing researcher, you will be primarily responsible
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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, Atmospheric and Oceanic Sciences, Geosciences, Computational Science and Engineering, or a related area is required.The position will involve developing models and algorithms for the evolution of inorganic
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Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments. Modeling dynamical systems
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distributed quantum computing. The center includes other quantum faculty, and conducts a wide range of collaborative quantum research in the areas of quantum computing, quantum algorithms and complexity
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learning on large-scale HPC systems Scalable and energy-efficient AI training algorithms Image reconstruction, segmentation, and spatiotemporal modeling High-performance computing for large-scale AI and
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments