48 parallel-and-distributed-computing-"UNIS" Postdoctoral positions at Argonne in United States
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device operation. The project involves large-scale simulations on exascale computing resources to probe switching behavior while accounting for effects of defects, competing metastable phases, doping
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(electrochemistry, materials synthesis, or characterization) or computational simulations perspective, is required. Proficiency in Python programming is required. Familiarity with REST APIs is desirable. Master’s
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The X-ray Imaging Group (IMG) of the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in computational science and image processing to develop innovative methods
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, in Electrical Engineering and Computer Science or related field obtained within the last five years. Experience with X-ray physics or optical wave modeling. Proficiency in programming with Python
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to make our laboratory a safe, welcoming, inclusive, and accessible environment where all can thrive. Preferred Qualifications: Experience in TEA and LCA (e.g., using GREET model). Skills in computer
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R
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Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead efforts to discover and design quantum emitters with desirable properties for quantum information science (QIS
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focus on further advancing the ATTA technique. The Physics Division has an active and broad-ranging program at the intersection of nuclear and atomic physics including a strong focus on fundamental
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-inspired research relevant to microelectronics. The candidate will be part of a highly interdisciplinary project involving X-ray scientists, physicists, materials scientists, and computational scientists
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addition to conventional tools such as XRD, BET, XRF, SEM, TEM, etc. Collaborate with computational modeling and artificial intelligence/machine learning teams to improve battery performance, using rational design