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the data science, process analytical technology, and chemical processing domains to address technology challenges for raidoistoope production and application. Major Duties/Rsponsibilities: Develop and
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. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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analytics, including correlation analysis and machine learning techniques. Preferred Qualifications: Experience with microstructure characterization techniques (SEM, EBSD, TEM, XRD). Experience in mechanical
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monitoring in manufacturing environment Develop modular, extensible workflows for data processing Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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preparation of well-characterized target compounds. Apply a range of analytical and characterization techniques to evaluate chelator structure, affinity, selectivity, and metal complexation, including radio-TLC
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis
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with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant