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the Quantum Heterostructures Group in the Foundational & Quantum Materials Science Section, Materials Science and Technology Division, Physical Sciences Directorate at Oak Ridge National Laboratory (ORNL). As
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challenges facing the nation. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral
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experimentally validating simulations efforts for quantum spin systems. This position resides in the Correlated Electron Materials Group in the Materials Science and Technology Division, Physical Sciences
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sensor research and development for energy applications, with a focus on advanced manufacturing technologies. The MSA group consists of staff members with backgrounds in mechanical engineering, materials
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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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challenges facing the nation. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral
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Requisition Id 15553 Overview: We are seeking a Postdoctoral researcher in data quality assessment and control and sensor network optimization who will focus on R&D of sensor network design. This
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methods towards improving our understanding of unique target materials. You will be working with scientists, engineers, technicians, and safety and quality assurance staff to support material testing and
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seeking to advance the separation science and technology for clean energy applications. Work with the Separation Technologies team to support a broad range of program development opportunities in the field
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Scientist you will be responsible for: Developing high-quality code following best practices in the community for documentation, provenance, version control, etc. Participating in research projects in AI