52 computer-programmer-"https:" "https:" "https:" "https:" "https:" "Data driven Materials Modeling" research jobs at Argonne
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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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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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Publications: 1. P. Chen et al., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1. 2. P. Chen et al., Optics
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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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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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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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Argonne National Laboratory has a long-standing tradition of attracting top early career talent through the Named Fellowship Program. These prestigious fellowships are awarded internationally each
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to a collaborative, multidisciplinary research program focused on the chemical recycling of polymers and organometallic catalysis. You will work alongside scientists with diverse expertise to design
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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