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The Chemical Sciences and Engineering Division invites applications for a Postdoctoral Appointee to contribute to innovative research at the intersection of computational catalysis, quantum
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camera technology and multiplexed readout systems for quantum information science applications. In this role, you will join a multidisciplinary team spanning several Argonne divisions and contribute
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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, or network-based modeling of infrastructure or industrial systems. Familiarity with high-performance computing, cloud computing, or parallel computing environments for training models and solving optimization
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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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at the Large Hadron Collider (LHC). The successful candidate will contribute to a broad research program that includes physics analysis, detector performance studies, experiment operations, and upgrade
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. The candidate will assume a primary role in spearheading the development of a comprehensive growth, synthesis, and innovative characterization experimental program specifically tailored to diamond
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nitrogen-vacancy (NV) diamond quantum magnetometry for high-energy physics experiments. The HEP Division performs cutting-edge research leveraging advanced detector development, high-performance computing