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contributions to the development of the Time-of-Flight system of the EPiC Detector for the Electron-Ion Collider, including leadership of multi-institutional efforts to develop prototype assemblies. Performing
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infections using electronic phenotyping, supervised machine learning, live Epic/FHIR implementations for silent deployment, and multi-site data coordination. https://reporter.nih.gov/search
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performance and degradation of electrolysis in dependence on different operating modes Your Profile: Completed Master’s degree in chemical engineering, computational engineering, computational mathematics, data
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