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Integrate models across platforms and workflows; manage inputs/outputs and ensure reproducibility Analyze simulation and experimental datasets; extract insights and quantify sensitivities and uncertainties
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications
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rigorous experimental evaluation. Advancing federated learning methods that enable distributed and privacy-aware training and adaptation of foundation models. Using modern AI tools to accelerate research
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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
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Overview The Argonne Wakefield Accelerator (AWA) Group in the High Energy Physics Division at Argonne National Laboratory seeks a postdoctoral research associate to conduct experimental and
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related to next generation cathode material synthesis for lithium-ion and sodium batteries. The selected individual will work under supervision and will assist the Lead PI on developing experimental methods
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design, develop, and evaluate AI-driven scientific visualization assistants that support intuitive, context-aware interaction with large-scale simulation and experimental data. The postdoc will focus
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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Argonne National Laboratory invites applications for a postdoctoral research position in experimental physics, with a focus on advancing superconducting particle detector technology for next
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The Medium Energy Physics (MEP) group at Argonne National Laboratory invites applications for multiple experimental postdoctoral researcher positions. Depending on your background, your portfolio