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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
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activities. This is an exciting opportunity to work within a collaborative group with deep expertise in silicon detectors, Trigger/DAQ (TDAQ) systems, software, and computing. The Argonne ATLAS group plays a
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The Argonne team is seeking two highly motivated postdoctoral researchers to help shape the next generation of secure, scalable, and continuously learning AI systems for biomedical discovery
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that can guide experiments, improve efficiency, and strengthen collaboration between computation and experiment. Key Responsibilities Develop machine learning-ready data resources for materials by
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collaboration and innovation. Position Requirements This level of knowledge is typically achieved through a formal education in Statistics, Machine Learning, Computer Science, Logistics/Supply Chain, or a related
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) at Argonne National Laboratory to advance learning-enabled imaging methods. This position offers a unique opportunity for candidates with backgrounds in electrical engineering, computer science, applied
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Postdoctoral Researcher in artificial intelligence and machine learning (AI/ML) for advanced tuning and diagnosis of particle accelerators. The Accelerator Operations and Physics (AOP) Group
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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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processes Implement models and perform numerical simulations Analyze and interpret simulation and experimental data Integrate AI tools and workflows to enhance modeling and accelerate learning Collaborate
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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