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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence
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Developing QA documents (Work Instructions, Test Plans) Extracting images from mechanical models for documentation Contributing to project and engineering work process documentation What is Required: Full-time
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for binding critical minerals and materials. The postdoc will be part of a collaborative team of researchers in the Molecular Foundry from the Biological Nanostructures, Data Science and Infrastructure, Imaging
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spins to correlated spin arrays and prototype device architectures. This position contributes to the development of molecular quantum materials within a DOE user facility environment, leveraging
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methodology Assist with code optimization and integration into Department of Energy (DOE's) applications running on the exascale computer systems with GPU accelerators We are looking for: PhD or equivalent
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in the preparation of proposals for funding. Mentor graduate students and postdocs. We are looking for: PhD or equivalent in a Computing Science or Computer Engineering-related scientific discipline
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reasoning over large scientific data sets. Developing theories for materials synthesis and degradation. Preparing presentations and reports. Writing peer-reviewed journal articles. We are looking for: PhD in
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tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics, or a related numerical field. Programming experience
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of world-class science. You will perform varied tasks essential day-to-day operation of the plant facilities systems, complete preventive maintenance, make small and complex equipment repairs, monitor and