2,156 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" positions at University of Michigan
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/walking, as well as lifting, positioning, pushing, and/or transferring patients. Desired Qualifications* Completion of a Certified Nurse Aide or Certified Medical Assistant program; basic computer skills
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of employment. Learn more about the work modes . Work Schedule Full Time hours, 40 hours per week, weekday schedule will vary depending on location/clinic. Work Locations Ann Arbor The candidate selected
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time, and for any reason, throughout the course of employment. Learn more about the work modes . Work Locations Michigan Medicine Health Advancement, Ann Arbor, MI 48109 Additional Information NOTE: A
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change at any time, and for any reason, throughout the course of employment. Learn more about the work modes . Work Schedule Monday- Friday with some evening shifts and rotating Saturdays Union Affiliation
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are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes . Work Schedule This position will primarily support work M-F during normal
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are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes . Work Schedule Full Time hours, 40 hours per week, weekday schedule will vary
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at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work
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change at any time, and for any reason, throughout the course of employment. Learn more about the work modes . Background Screening The University of Michigan conducts background checks on all job
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time, and for any reason, throughout the course of employment. Learn more about the work modes . Additional Information This is a half-time, term-limited position through March 2027. Extension
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dedicated colleague to teach a wide range of undergraduate statistics and data science courses, especially modern methods of applied statistics and hands-on data analysis, in an engaging and dynamic manner