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at the Large Hadron Collider (LHC). The successful candidate will contribute to a broad research program that includes physics analysis, detector performance studies, experiment operations, and upgrade
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of both hardware and software tools for operando characterization under electrochemical conditions, as well as the management and analysis of large experimental datasets. The successful candidate will
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. Experience developing, manipulating, and analyzing large data sets. Understanding of energy technologies and their supply chains. Experience working with Argonne’s R&D GREET model and BatPaC battery cost model
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. This position will contribute to the Forge project, which is focused on developing advanced multimodal AI capabilities that can learn across distributed data environments without requiring sensitive data to be
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and modeling teams using data from the Atmospheric Radiation Measurement (ARM) User Facility including the Bankhead National Forest (BNF) and Desert-Urban System Integrated Atmospheric Monsoon
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Argonne National Laboratory invites applications for a Postdoctoral Researcher position in Superconducting Detector Development and CMB Instrumentation. This role focuses on advancing large arrays
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design, develop, and evaluate AI-driven scientific visualization assistants that support intuitive, context-aware interaction with large-scale simulation and experimental data. The postdoc will focus
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to large single-crystal YIG spheres for optimizing magnon target mass and improving axion detector sensitivity. Develop detector sensing demonstration experiments for measuring the quantum efficiency and
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, surrogate modeling, clustering, anomaly detection, or probabilistic modeling. Proficiency in Python/Julia/R and scientific computing/data analysis tools and related libraries. Experience working with large
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be