58 development "https:" "https:" "https:" "University of Houston" research jobs at Oak Ridge National Laboratory
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-class S&T products for sensitive national security missions. The selected candidate will support research efforts in signal processing and analysis, with an emphasis on the development of novel algorithms
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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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Engineering Development Center, ORNL’s other nuclear facilities, and an assemblage of world-leading scientists and engineers. Please visit https://www.ornl.gov/directorate/isotopes for more information about
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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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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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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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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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physical characterization techniques (differential scanning calorimetry, dynamic light scattering, small angle neutron and/or x-ray scattering) to characterize the DIBs; and (3) Develop/implement image
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through the High Flux Isotope Reactor, the Radiochemical Engineering Development Center, ORNL’s other nuclear facilities, and an assemblage of world-leading scientists and engineers. Please visit https
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/Responsibilities: Develop and apply AI foundation models for hydrological and Earth system modeling, with emphasis on improving predictive capabilities for compound flooding in coastal regions. Design and implement