71 software-formal-method-phd positions at Oak Ridge National Laboratory in postdoctoral
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performance and detect anomalies Develop AI-driven predictive maintenance strategies to anticipate system failures or performance degradation Use AI/ML methods to optimize thermal system design parameters and
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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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. 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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, 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 in physics or a related
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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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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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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