61 data "https:" "https:" "https:" "https:" "https:" "Inria" Postdoctoral positions at Oak Ridge National Laboratory
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universities to address project objectives. Present research results within the project and at national and international conferences, and publish findings in peer-reviewed journals, and datasets in DOE data
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for geothermal casing related harsh environments applications. A background in polymer chemistry research or related fields, composite material development, material science, and data analysis is preferred. Strong
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to design and implement experiments, perform data analyses, and interpret experimental results. Excellent interpersonal, oral, and written communication skills. Preferred Qualifications: Demonstrated
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participation, and dissemination of research results. Adhere to requirements for protecting proprietary or sensitive information and follow ORNL cybersecurity policies and guidelines. Basic Qualifications: Ph.D
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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improve access to divertor-relevant target exposure conditions. Validate simulation results against experimental data and constrain code inputs to reduce uncertainty in predictions for future experiments
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science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information
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evolution, phase stress, and defect evolution using advanced data analysis tools. Perform alloy fabrication and processing (e.g., arc melting, heat treatment) and relate processing to performance. Apply
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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. Excellent analytical skills with high attention to detail. Experience with geospatial data visualization tools such as ArcGIS, Cesium, or similar. Familiarity with urban-scale building energy modeling