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Argonne National Laboratory invites applications for a Postdoctoral Researcher position in Superconducting Detector Development and CMB Instrumentation. This role focuses on advancing large arrays
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Argonne National Laboratory’s Accelerator Science Division is seeking a Postdoctoral Appointee to contribute to the development of a Sub- THz Collinear Structural Wakefield Accelerator
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The Applied Materials Division, Process R&D and Scale up Group at Argonne National Laboratory is seeking a Postdoctoral candidate to conduct general research in material science and electrochemistry related to next generation cathode material synthesis for lithium-ion and sodium batteries. The...
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of these systems are insufficient to cover the diversity of human-driven experimental activities. The development of multi-appendage, dexterous robots with embodied intelligence is a key to closing this gap
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enable physics-informed AI agents that accelerate discovery in catalysis science. The successful candidate will focus on the development and application of machine learning and AI approaches to analyze
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, competitive, and energy-efficient U.S. manufacturing systems. The appointee will be expected to lead core model development and as needed, help expand capabilities in co-optimization of industrial end-use and
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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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The Chemical and Fuel Cycle Technologies division is seeking a Postdoctoral Appointee to join an R&D team conducting use-inspired research supporting the development of molten salt technologies
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of experimental quantum communication hardware development, optical memory qubit characterization, and fiber-based networking demonstrations using novel memory qubits. The goal is to employ the natural telecom
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and integrate emerging AI techniques (e.g., agentic workflows, LLMs) into scientific problems, ensuring methods effectively solve real domain challenges. Advanced Model Development: Design and debug