44 phd-computational-intelligence Postdoctoral positions at Oak Ridge National Laboratory
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high level of scientific productivity. Ensuring compliance with environment, safety, health, and quality program requirements. Maintaining a strong commitment to the implementation and perpetuation
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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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timely manner Maintain strong commitment to the implementation and perpetuation of ORNL core values and ethics Basic Qualifications: A PhD related to computational or theoretical physics, chemistry
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Requisition Id 16104 Overview: The Quantum Heterostructures Group is seeking outstanding candidates for a postdoctoral position in quantum information science. You will conduct experimental
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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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, health, and quality program requirements. Maintain a strong commitment to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors, priorities, and
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in Computer Science or a related discipline. A strong background in scientific data