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, supported by: Multiscale modeling (material (molecular) → process → manufacturing (scale up)) Data-informed experimentation Selective use of AI/ML and big-data techniques where they add real value
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of computational scientists, computer scientists, experimentalists, materials scientists, and conduct basic and applied research in support of the Laboratory’s mission. Engage with the broader community
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degree with a minimum of 4 years of experience, or a PhD in Electrical Engineering, Physics, Computer Engineering, or related field Experience in research environments focused on advanced SPM or equivalent
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in high-performance computing and data analytics with applications in a large variety of science domains and NCCS is home to some of the fastest supercomputers and storage systems in the world
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a related field with 7+ years of experience or a PhD in mathematics, computer science, engineering with relevant experience. Preferred Qualifications: Experience with mesh generation/CFD applications
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a related field with 7+ years of experience or a PhD in mathematics, computer science, engineering with relevant experience. Preferred Qualifications: Experience with mesh generation/CFD applications
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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
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capabilities for advanced nuclear materials systems. In addition, this work includes developing processes that connect mechanical and thermophysical testing data with the microstructures of ceramic and metallic
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by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in physics or a related field completed within the last 5 years
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services, databases, infrastructure, and associated system components. Develop software (front-end and back-end), APIs, services, and microservices; design database schemas; manage data flows and storage