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by publications in peer-reviewed journals. Ability to work effectively both independently and within interdisciplinary, collaborative research teams, including mentoring students, managing multiple
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effectively. Ability to manage multiple technically demanding projects simultaneously, prioritize competing deadlines, and maintain high-quality work in a fast-paced research environment. Demonstrated ability
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to bring strong expertise in scalable deep learning, high-performance computing (HPC), scalable data management, Linux environments, and production-quality scripting for HPC workflows. Major Duties
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communication and program management skills are required. This position resides in the Carbon Fiber Technology Facility (CFTF) and the work is performed at the Manufacturing Demonstration Facility (MDF) in
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of renewable energy and energy efficiency management and projects excellent quantitative and analytical background acquired through research, which can be applied to conduct research analyses on on-site energy
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-efficient building systems, thermal-fluid processes, industrial heating applications, data center thermal management, and other emerging energy technologies. Develop and operate experimental facilities
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or program datasets. Proficiency in statistical programming and data analysis tools: R, Python, Stata, or SAS SQL/database management preferred. Ability to clean, harmonize, and analyze complex datasets from
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on the physical metallurgy of non-ferrous alloys for various applications including aerospace, automotive, and thermal management applications. Projects will include application of physical metallurgy principles
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supercomputing resources. The candidate will also contribute to the development of large-scale identity and key management solutions. We are a leader in computational and computer science, with signature strengths
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MSTD on the physical metallurgy of aluminum alloys for various applications including automotive, aerospace, and thermal management. Projects will include application of physical metallurgy principles