884 computer-programmer-"https:"-"CNR" "https:" "https:" "https:" "https:" "U.S" positions at University of Arkansas
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Nursing, Associate’s degree in Nursing, Diploma RN, or Master’s degree in Nursing. Must be a graduate of an accredited RN nursing program Valid Registered Nursing License Minimum of 1 year of Registered
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Department of Physical Therapy at the UAMS Northwest Campus in Fayetteville, Arkansas. You have the opportunity to join an innovative and successful program with strong institutional and community support
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; assist with all program activities; complete student evaluation forms; attend orientation and staff meetings; assist instructors in classroom activities; assist in tutoring students during the evening help
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to pre-tax supplemental Retirement. Qualifications: Required: Graduate of an accredited Nursing Program with Associates Degree, Nursing Diploma, Bachelors in Nursing, or Master's in Nursing. Valid RN
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to work other than normal office hours, nights, and weekends; Ability to train others, and work independently and as a member of a team; Ability to meet multiple program deadlines and manage multiple tasks
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an educational program that provides specialized certification and is regulated by either the Arkansas State Board of Nursing or the Arkansas State Medical Board. An APRN/PA manifests a high level of expertise in
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for the position, please click the Apply link/button. If you have a disability and need assistance with the hiring process and require reasonable accommodations, please contact the Division's Office of Program
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, or formal educational equivalent. Successful completion of the Medical Assistant training program. Ability to perform point of care testing, draw and collect blood specimens, and prepare for laboratory
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-3180. Department: COSMOS - Provisional Positions Department's Website: https://cosmos.ualr.edu/ Summary of Job Duties: The Extra Help Assistant will help develop socio-computational models to advance our
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Website: https://cosmos.ualr.edu/ Summary of Job Duties: The Extra Help Assistant will help develop socio-computational models to advance our understanding of cyber campaigns run on social media grounded in