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and post-DFT methods) for generating datasets to train AI models leveraging DOE’s HPC platforms Develop new methodologies that can describe both atomic and spin relaxation accurately but at a much
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workflows to enable AI-readiness at scale. You will work on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed
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, 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 degree in Mechanical
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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. Design and evaluation of ephemeral, user-configurable, and composable data and storage systems. Design system-level approaches for time-sensitive or data-intensive processing of data originating
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success Basic Qualifications: A Ph.D. in Condensed Mather Physics, Materials Science and Engineering, or
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. This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf
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performance and the availability of funding. Candidates are asked to submit a detailed cover letter describing their experience relative to the duties and qualifications described in this posting with
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mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation. To obtain this credential
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accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted