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scientists, engineers, and facility operators to integrate AI seamlessly into experimental and computational pipelines. Demonstrate the effectiveness of dynamic workflows in representative use cases such as
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.) to enable real-time process monitoring of the Directed Energy Deposition (DED) printing process. A background in sensors, instrumentation, and data analytics is preferred. Strong communication and program
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Requisition Id 15815 Overview: The Workflows and Ecosystem Services (WES) group under the Advanced Technology Section (ATS) of the National Center for Computational Sciences (NCCS) is seeking a
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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across diverse clients. You will use Frontier's computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also
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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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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