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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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the application of these methods and tools to complex issues in the domains of environmental, water, and energy system analysis. Position Requirements Recent or soon-to-be completed (typically within the last 0-5
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materials characterization (e.g., atomic force microscopy). Key responsibilities include designing and executing experiments, analyzing and interpreting complex datasets, and disseminating results through
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mechanisms of photoinduced charge transfer and spin state conversion across a wide spectrum of systems, including small transition metal complexes and donor-acceptor systems. By performing state-of-the-art
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and to communicate complex results effectively in writing and presentations. Record of peer-reviewed publications commensurate with career stage. Commitment to Argonne’s core values and safe work
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees
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photonic platforms for hybrid quantum systems. The role offers a unique opportunity to engage in advanced materials synthesis, nanofabrication, and multimodal characterization using Argonne’s world-class
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales. Key Responsibilities Design, implement, and validate physics-informed AI/ML
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This is an opportunity for a knowledgeable and creative individual to be part of a team using artificial intelligence and high-performance computing to evaluate the state of health (SOH