311 high-performance-quantum-computing-"https:"-"https:" positions at Oak Ridge National Laboratory
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safety practices. Foster a collaborative, team-oriented work environment. Basic Qualifications: High School Diploma or equivalent. 2-4 years of relevant administrative, front desk, customer service
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with training machine learning models on high performance computing infrastructures leveraging GPU accelerators. Experience in the development of project research proposals. Ability to function well in a
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centered on Microsoft Azure and related AI cloud technologies with High Performance Computing (HPC) for on premise AI environments and Azure, AWS, and GCP for off premise environments. Major Duties
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Structure and Nuclear Astrophysics research program. Major Duties/Responsibilities: Conduct original independent research on the physics of exotic nuclei. Provide technical leadership for conceptualization
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to specifications using precision instruments. Read and understand Geometric Dimensioning & Tolerancing (GD&T) and technical drawings. Program, set-up and operate Coordinate Measurement Machines (CMM) and utilize a
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. They will work closely with scientists, technicians, and engineers on technical projects in support of the DOE Isotope Program and other DOE missions. This program offers opportunities for professional growth
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for isotope enrichment. They will work closely with scientists, technicians, and engineers on technical projects in support of the DOE Isotope Program and other DOE missions. This program offers opportunities
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policy. The TSSC Team Manager will lead the Oak Ridge National Laboratory’s SCIF Technical Security Team and Program regarding TSCM and TEMPEST activities. This position combines advanced technical skills
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division
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platforms that transform how buildings are designed and constructed. The successful candidate will contribute to a UT-ORII Convergent Research Initiative (CRI) aimed at enabling affordable, resilient, high