11 atomic-physic Postdoctoral positions at Oak Ridge National Laboratory in United States
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. This position resides in the Quantum Heterostructures Group in the Foundational & Quantum Materials Science Section, Materials Science and Technology Division, Physical Sciences Directorate at Oak Ridge National
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national scale. Lead and participate in research partnerships with industrial and academic partners. Lead or contribute to proposals for future research related to clean and renewable energy development
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Requisition Id 15813 Overview: We are seeking a highly motivated postdoctoral researcher with a strong background in sensor integration, data acquisition, and in situ process monitoring
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. The successful candidate will have the opportunity to assist ORNL scientists involved in these efforts, to gain expertise in biokinetic and dosimetric modeling, and to assist and eventually lead in the preparation
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Physical Sciences, such as Geochemistry, Chemistry, Geology, Materials Science, or related disciplines completed within the last 5 years. Strong background in atomic-scale simulation. Preferred
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for simulating atomic nuclei, as well as preparing data and using machine learning models for investigating how the properties of atomic nuclei connect to fundamental questions in physics, such as constraining
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. Research will involve growth of single crystals and measurements to understand their structural and physical properties including magnetism and thermal transport, as well as helping to identify new magnetic
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-building energy performance and systems integration, deployment, and analysis in support of the DOE mission. Staff members lead and participate on teams focused on R&D and deployment of energy-efficient
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methods. The successful candidate will play a leading role in investigating how the properties of atomic nuclei connect to fundamental questions in physics, such as the origin of symmetries and symmetry
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for CT. Major Duties/Responsibilities: Lead research on sparse-view and limited-angle CT algorithms for scientific and industrial applications. Develop and apply ML/AI-driven computational imaging methods