66 engineering-computation "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral positions at Oak Ridge National Laboratory in United States
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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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Science, Computer Science, Applied Mathematics and Statistics, Electrical and Computer Engineering, Biomedical Engineering, or a related field. Experience with a deep learning framework like PyTorch. Strong
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challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
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to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, while working with the world’s fastest computers, and disseminate innovative results through
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Requisition Id 15217 Overview: The Multiscale Biomedical Systems group in the Advanced Computing in Health (ACH) section in Computational Sciences and Engineering Division (CSED), Computing and
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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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through papers, artifacts, and presentations at top-tier venues. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, a physical/computational science discipline (e.g., physics, chemistry
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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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algorithms at scale on ORNL's computational resources, including the Frontier supercomputer, addressing critical challenges in science and engineering. Communicate and coordinate experimental results with
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across diverse clients. You will use Frontier's computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also