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relationships, and distributed optimization of machine learning workflows. Collaborating with world-class scientists, you will enhance your expertise in resource optimization, scalable computing techniques
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areas central to dataflow and tensor optimization. Hardware/Software Co‑Design : Familiarity with architectural simulators (e.g., Gem5, SST) or HDLs. Quantum / Analog Computing : Exposure to quantum
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central to dataflow and tensor optimization. Hardware/Software Co‑Design: Familiarity with architectural simulators (e.g., Gem5, SST) or HDLs. Quantum / Analog Computing: Exposure to quantum programming
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with
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Requisition Id 17231 Overview: We are seeking a Postdoctoral Research Associate who will focus on the development, application, and optimization of an active learning workflow for dataset
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to additive manufacturing (AM), virtual manufacturing, material characterization, topology optimization, and real-time sensing. This position resides in the Computational Sciences and Engineering
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learning, optimization, scientific computing, domain sciences, and high-performance computing. The candidate will have opportunities to work with world-class computing resources, including ORNL’s
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management, execution orchestration, and optimization across quantum and classical computing resources. Conduct hardware-software and application-system co-design by considering interactions among
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, optomechanics, optical cavities, and/or photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of
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five-year mission of the ORNL Quantum Science Center (QSC) to establish a quantum-accelerated computing ecosystem for scientific applications. The successful candidate will develop, test, and evaluate