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successful candidate will conduct research focused on meso- and macroscale mathematical modeling of next-generation batteries, while leveraging advanced artificial intelligence (AI) tools to accelerate
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methods with optimization and decision-support models. Background in one or more of the following: time-series analysis, neural networks, forecasting, uncertainty quantification, sensitivity analysis
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(BCDI), Laue microdiffraction, ptychographic laminography, and X-ray photon correlation spectroscopy (XPCS) to study strain, dislocation networks, voids, and interfacial morphology. Develop in-situ and
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potential impact across quantum networking, communications, and computing. Research Focus Design and fabricate superconducting devices that leverage the nonlinear kinetic inductance of thin superconducting
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photonic quantum devices for a heterogeneous quantum network, including but not limited to superconducting qubits, microwave-optical quantum transducers, etc. The postdocs will design the devices, fabricate
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Responsibilities : Spearhead the research and development of predictive models and strategic tools designed to support decision making in strengthening both domestic and international supply chains, particularly
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Argonne National Laboratory is seeking a postdoctoral researcher with expertise in life-cycle analysis, industrial process modeling, and critical minerals and materials assessment. The appointee
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characterization, and machine learning. The role offers the opportunity to leverage Argonne’s world-class scientific capabilities and engage with a strong network of internal and industry collaborators. Position
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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learning (ML) to address future physics and detector challenges. Current physics interests include Standard Model measurements and searches for new phenomena. We welcome applicants who are excited