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seeking to advance the separation science and technology for clean energy applications. Work with the Separation Technologies team to support a broad range of program development opportunities in the field
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. Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, engineers, and physicists conducting basic and applied AI/DL research
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science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
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industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE
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experts. You will bring creative thinking, teamwork, and machine learning skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and
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through papers, artifacts, and presentations at top-tier venues. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, a physical/computational science discipline (e.g., physics, chemistry
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Science, Computer Science, Applied Mathematics and Statistics, Electrical and Computer Engineering, Biomedical Engineering, or a related field. Experience with a deep learning framework like PyTorch. Strong
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/Responsibilities: Utilize techniques such as optical microscopy, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM) for microstructural
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to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, while working with the world’s fastest computers, and disseminate innovative results through
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, and measure success. Basic Qualifications: Ph.D. in Polymer Science and Engineering, Polymer Chemistry, Chemical Engineering, Materials Science and Engineering, or a closely related field, obtained