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Field
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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developing computational infrastructure, designing machine learning segmentation and classification pipelines, creating visualization and UI tools, processing, storing, and disseminating large datasets, and
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environment for NERSC's 11,000+ users. The SSG is responsible for NERSC's storage portfolio, including large scale high capacity parallel file systems and archival storage systems with an eye towards balancing
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), parallelization (running loop iterations in parallel), enhancing data locality by fusion, and blocking (i.e. accessing arrays in a way that improves temporal and spatial data locality). A large number of
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in
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within a multi-disciplinary research environment consisting of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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Requirements: The candidate must be able to demonstrate a deep knowledge of supercomputing software development for massively-parallel computer architectures, and expertise in working with large-scale software
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to the discovery process through algorithm design and development of effective computing techniques What We're Looking For Education and Experience Required: Master’s degree in chemistry, engineering, math, physical
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 29 days ago
developing computational infrastructure, designing machine learning segmentation and classification pipelines, creating visualization and UI tools, processing, storing, and disseminating large datasets, and