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image reconstruction methods, signal processing techniques, and data analysis pipelines for novel X-ray imaging modalities, including ghost imaging, quantum-enhanced imaging, and other correlation-based
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physics. Participation in detector research and development, especially for low-latency event selection in trigger systems. Development of new artificial-intelligence and machine-learning techniques
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image reconstruction methods, signal processing techniques, and data analysis pipelines for novel X-ray imaging modalities, including ghost imaging, quantum-enhanced imaging, and other correlation-based
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physics. Development of new artificial-intelligence and machine-learning techniques for high-energy and nuclear physics. Close interaction with our collaborators in the EIC and the BNL theory group will be
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strong knowledge of superconductivity and quantum information science; You have performed low temperature electrical transport measurements and data analysis. You work effectively in a collaborative team
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experiment at the EIC. The program includes data analysis involving polarized targets at Jefferson Lab as well as full detector and physics simulations for ePIC. In addition, the candidate will collaborate
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radiation-induced reaction kinetics and mechanisms, including pulse radiolysis experiments on ACER’s accelerator facilities. Data analysis (e.g., fitting transient absorption data, making plots of spectra
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. Essential Duties and Responsibilities: Planning experiments, preparing samples, and conducting experiments at LEAF. Data analysis (e.g. fitting transient absorption data, making plots of spectra). Writing
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will collaborate closely with NSLS-II staff while developing cutting edge sample preparation and data analysis techniques that enable the next generation of the XCFS methodology. In addition
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proposals for ongoing research program Required Knowledge, Skills, and Abilities: Ph.D. in physics or related discipline within the last 5 years Strong background in condensed matter physics Data analysis