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, collaborate with interdisciplinary teams, publish in leading scientific venues, and contribute to emerging QHPC software and system technologies. Major Duties/Responsibilities: Develop and evaluate
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. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from the SPRUCE (Spruce and
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, electrical engineering, or a related discipline obtained in
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computing, with a particular emphasis on methods tailored to study nonequilibrium quantum many-body systems. The position offers an exciting opportunity to contribute to cutting-edge research
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. Basic Qualifications: A PhD in Materials Science & Engineering, Physics, Chemistry, or a related field completed within the last 5 years A minimum of 2 years of post-Ph.D. experience utilizing
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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Service. Basic Qualifications: Applicants must have either received their PhD in a STEM or National Security field no more than 5 years prior to or expect to be awarded their PhD no later than 6 months
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represents expertise in nuclear materials synthesis and analysis, deployment of advanced analytical methods including crystallography, imaging, spectroscopy, physical property analysis, neutron scattering, and
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implementation of constitutive models within commercial and/or open-source finite element software is required. Preferred Qualifications: Demonstrated expertise in multi-physics FE simulations is preferred
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in chemical engineering, chemistry, mechanical engineering, civil