67 algorithm-development "https:" "Simons Foundation" Postdoctoral research jobs at Argonne
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to develop innovative technologies to improve the efficiency of resource utilization; to minimize our dependence on imported materials; and to enhance our national security. This position is broadly focused
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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The Microscopy group in X-ray Science Division of Advanced Photon Source at Argonne National Laboratory is seeking postdoctoral researchers to work on cutting-edge ptychography technique development
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through the design and synthesis of nanoscale epitaxial oxide thin films. This position supports a three-year Laboratory Directed Research and Development (LDRD) project focused on developing scalable
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readout and controls (e.g., SQUID-based time- or microwave-multiplexed systems) with beamline data acquisition and control (EPICS/Bluesky). Develop and maintain data acquisition, calibration, and analysis
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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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mixed/reduced precision into existing applications relevant to ALCF's mission Developing and maintaining tools and libraries that facilitate the adoption of mixed/reduced precision computing in
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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We are seeking a highly motivated and flexible postdoctoral researcher to join the Applied Materials Division (AMD) at Argonne National Laboratory to develop advanced methods for in situ and
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. Working within an interdisciplinary team, you will develop frameworks that connect atomistic features, mesoscale dynamics, and device-level performance. The effort will integrate heterogeneous data from