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following component failures Experimentally validating the AI/ML methods on the ATLAS linac at Argonne National Laboratory Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years
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, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven scholarly work or industry
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and techniques to synthesize these new materials. The candidate needs to be familiar with electrochemical testing and evaluating these materials. Position Requirements Recent or soon-to-be-completed PhD
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-completed PhD (typically completed within the last 0-5 years) in chemical engineering, environmental engineering, or similar degree. Experience with data collection, processing, analysis, and presentation
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instrument proposed under a DOE Major Item of Equipment (MIE) effort. Building on two decades of APS XRS capability (including the LERIX program at 20-ID) and recent commissioning work at Sector 25
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monitoring and gradient tests. Participate in training opportunities, including attending the US Particle Accelerator School (USPAS). Position Requirements PhD completed in the past 5 years or soon to complete
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limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory. The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable
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, design of experiments, image and data processing. Position Requirements Recent or soon-to-be-completed PhD with strong background in Physics or Materials Science (within the last 5 years) Physics
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samples and characterize dynamic behaviors. The candidate will be part of a highly collaborative team and actively interact with other groups, including optics, computation, and time-resolved research