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. Collaborate with a multidisciplinary team of engineers, computer scientists, and data scientists to put research insights into open-source software products. Publish research findings in leading academic
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interdisciplinary and collaborative team of engineers, analysts, and software developers. GAC works to develop and apply state-of-the-art energy system modeling techniques, software, and simulations for breakthrough
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manuscript preparation; use graphics and statistical software to analyze and present data; search pertinent scientific literature as needed. • Supervise other personnel in the laboratory; participate in
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letter, resume/CV to assist us with the review process. You may upload these documents to the application under CV/Resume. Required Education and Experience Appropriate PhD in a related field. Preferred
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advanced computational approaches, software engineering, high-performance computing, and an understanding of materials science, with an emphasis on metallurgy related to phase transformations and/or
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well as on the physics analysis of the GW data. Required skills and evaluation criteria The successful candidate is expected to have: Physics PHD Internationally recognized experience on research using the LIGO-Virgo data
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in professional organizations Basic Qualifications: A PhD in Mathematics, Applied Mathematics, Computational Science, or a related field completed within the last 5 years Preferred Qualifications
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Qualifications: PhD in related field (e.g., Kinesiology, Public Health, Psychology). Appropriate research background, as demonstrated by publications in peer-reviewed journals, grant funding, and stature
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professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant area with an education and a research track record in HPC/AI/edge systems and storage
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and