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Field
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algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
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Primary Duties & Responsibilities: Assists research studies with implementation of: existing algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 13 days ago
Scaling: Developing data-fusion algorithms that combine VSWIR spectroscopy with active radar/lidar, thermal, and atmospheric retrievals to scale plot- and tower-based flux measurements to pan-tropical
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Synthetic Aperture Radar (SAR) data for flood events. Developing algorithms to map flood extent, and event duration. Contributing development of data-fusion methods and modeling. Assisting with proposal
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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the intersection between quantum information and particle physics. The successful applicant will work in Professor Carlos Argüelles’ group on the development of new algorithms to encode and process particle physics
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algorithms and validate findings through computational studies, with the goal of publishing in leading operations research and management science journals. Job Requirements: Candidates must hold a Bachelor in
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acoustic propagation that are applicable to a wide range of ocean environments. (40%) Lead efforts to translate propagation and uncertainty models into computationally efficient algorithms that can be
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the theory of brain-inspired algorithms and apply them to complex, real-world problems. The successful candidate will join an interdisciplinary team of computer scientists, mathematicians, engineers, and
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at the interface of optimization, geometry, and machine learning Designing, implementing, and testing algorithms Engaging in scientific exchange with collaboration partners of the project Preparing reports