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The Nuclear Science and Engineering Division at Argonne National Laboratory seeks a Postdoctoral Appointee to conduct R&D on metallic materials for extreme environments relevant to nuclear energy
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-driven X-ray free-electron laser (XFEL) for attosecond science. The selected candidate will play a leading technical role in the design of a next-generation compact XFEL capable of producing agile
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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 to
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is extended yearly. Position Requirements A recent PhD (within 5 years) in computational chemistry, chemistry, materials science, physics, computational science, computer science, engineering, or a
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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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, benchmarking and deploy them for applications. The ideal candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning
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capable computers. The division aims to build lab-wide cross-cutting simulation application capabilities integrating with mathematics, computer science, domain science, and advanced computing architectures
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0-5 years in computer science, mechanical engineering, artificial intelligence, or related engineering disciplines Experience with state of the art AI methods for robotics Experience with robotics
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engineering, materials science, polymer science, physics, computer science, and/or data science Demonstrated accomplishments in materials informatics, scientific machine learning, or AI-guided
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range of core scientific capabilities, from nuclear physics and materials science to biology and advanced computer science. The Physics Division (PHY) at Argonne has a long and distinguished history in