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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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Requisition Id 17022 Overview: Oak Ridge National Laboratory (ORNL) is the world’s premier research institution, empowering leaders and teams to pursue breakthroughs in an environment marked by
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to the development of scalable and efficient implementations of these algorithms for state-of-the-art high performance computing facilities. Collaborate within a multi-disciplinary research environment consisting
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user interfaces. Record of peer-reviewed publications, conference presentations, or other research accomplishments. Experience working in multidisciplinary research environments involving both domain
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scientific journals in a timely manner. Maintain accurate and thorough experimental records and ensure compliance with environment, safety, health, and quality program requirements. Deliver ORNL’s mission by
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conferences. Supporting collective team goals, working harmoniously with colleagues, and maintaining rigorous compliance with environment, safety, health, and quality program requirements are fundamental
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-body systems and development of new neutron sample environment that allows time-resolved neutron scattering capabilities. This position resides in the Quantum Heterostructures Group in the Foundational
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Special Requirements: Applicants cannot have received
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develop and/or maintain strong relationships with ADD through active participation in professional societies. Ability to function well in a fast-paced research environment, set priorities to accomplish
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environment. Preferred Qualifications: Experience with AI/ML approaches for spatiotemporal or Earth system data, including transformers, multimodal learning, representation learning, or related architectures