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workflows in high-performance computing environments. Implement and develop prototype software to demonstrate feasibility of algorithms and then work with engineers to accelerate software in HPC environments
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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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Requisition Id 15854 Overview: We are seeking a research professional with fundamental knowledge in artificial intelligence (AI) who will focus on developing and applying AI algorithms to signal
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computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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intelligence, and architecture-aware algorithms that harness machines, ideas, and data to enable far reaching scientific breakthroughs. We develop computer innovations and advanced practical tools to address
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development of novel AI algorithms, it does require strong implementation skills, sound statistical judgment, and an ability to translate methods into reliable, maintainable, and well-documented pipelines
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation