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, reproducibility, and scalable data understanding Position Requirements PhD completed within the last 0–5 years (or near completion) in Computer Science, Computational Science, Visualization, Human–Computer
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This is an opportunity for a knowledgeable and creative individual to be part of a team using artificial intelligence and high-performance computing to evaluate the state of health (SOH
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of radiofrequency (MHz–GHz) nanoscale phenomena in systems relevant to microelectronics and quantum information science. Opportunities also exist for cross-platform studies integrating ultrafast TEM with ultrafast x
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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/modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a closely related field
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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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will require working on-site in Lemont, Illinois, 5 days a week Position Requirements Required skills, knowledge and experience: A recent or soon to be completed PhD within the last 0-5 years Molecular
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, computational physics, computational materials science, inverse problems, signal processing, x-ray science etc. are encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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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