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. Strong programming skills Familiarity with popular Deep Learning platforms such as PyTorch and TensorFlow Preferred Qualifications: Expertise in vision transformer or large language model Expertise in High
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, machine learning, geographical information sciences, and many other topics to help frame and solve the above problems on a national and global scale. The successful candidate will contribute to cutting-edge
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of the field through the development and use of machine learning, deep learning, and high-performance computing (HPC). This position resides in the Chemical Separations Group in the Separations and Polymer
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automation, machine learning, mobile robotics, process control, sensor processing, machine vision, and/or human machine interaction. This position will require working with external partners, corporations, and
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Postdoctoral Research Associate - Energy materials synthesis and exploration with neutron scattering
experiments in the physical, chemical, materials, biological and medical sciences. HFIR also provides unique facilities for isotope production and neutron irradiation. To learn more about Neutron Sciences
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the physical, chemical, materials, biological and medical sciences. HFIR also provides unique facilities for isotope production and neutron irradiation. To learn more about Neutron Sciences at ORNL, please go to
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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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journal articles. Robust interpersonal skills for effective team building and leadership, coupled with a strong commitment to scientific integrity. Eagerness to acquire new skills and explore new areas
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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well as artificial intelligence and machine learning techniques (AI/ML) with emphasis on electronic properties (charge and spin) of a range of materials important to the DOE mission, including the materials classes