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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking a Postdoctoral Appointee to contribute to the research, development, and manufacturing of advanced cathode materials for next-generation lithium- and sodium- ion batteries. This role provides a unique opportunity to...
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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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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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focus on our scientific program with CLAS12 (including the ALERT), Hall C and PRad-II at Jefferson Lab, and/or development of the EIC scientific program, including the development of a polarized light ion
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, computational physics and x-ray science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of the world’s largest supercomputers (Polaris
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reduction approaches and systems will be developed and implemented that operate close to instruments at the edge, and that leverage high-performance computing environments when needed. This position will be
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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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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