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The ALCF has an opening for a postdoctoral position in AI-assisted scientific visualization and intelligent data exploration. The successful candidate will join the Visualization and Data Analytics
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facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and
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accelerator structures, as well as conducting beam-based experiments. Key Responsibilities: Assist in the design and testing of beam diagnostic device operating at mmWave frequencies. Assist in conducting beam
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The Energy Systems and Infrastructure Assessment (ESIA) division provides the rationale for decision makers to improve energy efficiency. We develop and use analytic tools to help the U.S. achieve
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skills in terms that are universal and relatable to any computational project. To help our review committee fully understand your potential, please consider the following when preparing your materials
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journal/conference publications; the successful candidate will develop open-source packages and help disseminate research results to academic and industry community; and will draft research proposals and
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areas is preferred and will help the candidate succeed: X-ray absorption spectroscopy theory and modelling, and handling large synchrotron/X-ray datasets. Experience with vector databases (e.g. Pinecone
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technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will assist with data collection, analysis, and scenario modeling for a DOE-sponsored assessment
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hardware trend. To help bridge the gap, the Argonne Leadership Computing Facility (ALCF) invites applications for a postdoctoral appointment on the subject of mixed/reduced precision computing on modern
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-driven modeling (including ML/AI where appropriate) to help anticipate vulnerabilities and inform decision-making for energy deployment and national competitiveness. In this role you will : Conduct and