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a unique opportunity to develop cutting-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency
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, inference). Develop agentic AI systems and AI harnessing techniques to enhance model quality, resource optimization, and adaptive execution in diverse workflows. Investigate strategies to balance performance
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Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine learning/artificial
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technology by helping to attract, develop, and retain the workforce of actinide scientists to meet the needs of the nation. Topic of Interest This position is supported by the Department of Energy Isotope
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Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. If you have
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, reports. Seek membership in professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant area with an education and a research track record in
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at ORNL, along with computational tools for integrated atomistic modeling in support of materials research for extreme environments. The candidates will develop and apply advanced experimental
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of scientific AI. Focus Areas: Cross-Domain Interoperability: Develop common readiness templates, standardized metadata models, and APIs to enable seamless integration across diverse scientific domains
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network of universities, national laboratories, and industrial partners to develop a scientific ecosystem for fault-tolerant quantum-accelerated high-performance computing (QHPC). Major Duties
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professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant area with an education and a research track record in HPC/AI/edge systems and storage