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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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methods, as well as evidence synthesis, including coursework and research experience. 3. Programming experience using clinical research datasets (e.g., R, SAS, STATA). 4. Strong written and oral
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University School of Medicine to work on one of several ongoing NIH-funded projects to delineate virus-host factor interactions during enveloped virus entry and egress. The focus is on entry, uncoating and
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; Develop new LC-MS/MS methods as necessary; Calibrate, troubleshoot, and perform routine maintenance and repair of HPLC and Mass Spectrometer instruments; Analyze and interpret results of studies, review