71 computer-programmer-"https:"-"https:"-"UNIS" positions at Oak Ridge National Laboratory
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Requisition Id 15217 Overview: Oak Ridge National Laboratory (ORNL), the U.S. Department of Energy’s largest multi-program science and energy laboratory, has an extraordinary 80-year history
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response to upset conditions in the data centers. Operators are trained to the Computational Science Building Computer Center Operations Emergency Response Plan and Emergency Response Checklists. Upset
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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, safety, health, and quality program requirements. Uphold strong values and ethics in collaborative research. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values
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computing facilities available at ORNL and other DOE facilities. Independently plan and conduct simulations and work with experimentalists to help interpret spectroscopic results and help design new
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Learning skills. This position resides in the AI Operations Program office within the Application Development Division of the Information Technology Services Directorate. Our AI/ML models are heavily
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Learning skills. This position resides in the AI Operations Program office within the Application Development Division of the Information Technology Services Directorate. Our AI/ML models are heavily
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Requisition Id 15618 Overview: We are seeking a Computational Condensed Matter Physicist who will perform state-of-the-art numerical simulations of quantum magnets (i.e., quantum spin systems