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tools, including HPC for Project support, independent x-check analysis and R&D activities; establishing and implementing standards in the propulsion and fluid mechanics domain; providing the focal points
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The selected candidate must have applied before the application deadline online at the Lanbide webpage with code”162025012048”: : https://web.lanbide.eus/apps/OF_DETALLE_OFERTA_TRABAJO?LG=C&ML=OFEMEN1
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distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and
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Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine learning/artificial intelligence (ML/AI) techniques that incorporate
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Researcher to join Dr. Won C. Yim’s laboratory in the Department of Biochemistry & Molecular Biology. The successful candidate will contribute to a multi-institutional, federally funded project focused
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(HPC). Preference factors: - Experience with the C programming languages;; - Solid experience with the Linux operating system and scripting.; . Research FieldComputer science » InformaticsYears
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | about 2 months ago
. Learn and train on CODA software and its environment, namely development environment (IDE, debugger), pre/post-processing tools, mesh generation, AIRBUS HPC environment. Set-up and simulate simple
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, and resources to support pioneering research. Growth: Access professional development, leadership opportunities, and national visibility in HPC and research computing communities. Belonging: Be part of
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Postdoctoral Research Associate I (Computational Stellar Astrophysics) Posting Number req24359 Department Steward Observatory Department Website Link https://www.astro.arizona.edu Location Main Campus Address
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Data Processing Center. Prototyping and implementing data-science approaches and applications for LISA data. Planning and deploying HPC infrastructure for large-scale gravitational-wave data analysis