2,199 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "https:" "https:" "Dr" "P" uni jobs at Duke University
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, an endo-surgery center, and more. Position Title: Administrative Director – Heart Transplant Program Requisition Number: 402114940 – 260964 Location: Durham Duke Entity: Duke University Hospital Department
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Duke University, School of Law Program ID: Duke-Law-VAP2627 [#31241] Program Title: Visiting Assistant Professor Program Program Type: Non-regular rank faculty Location: Durham, North Carolina 27708
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an accredited BSN or Associate's Degree in Nursing or Nursing Diploma program. Exception: Registered nurses hired between July 1, 2014 and April 11, 2021 without a Bachelor's degree in Nursing (or higher
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other related duties incidental to the work described herein JOB ELIGIBILITY REQUIREMENTS Work requires graduation from an accredited BSN or Associate's Degree in Nursing or Nursing Diploma program
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retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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support to enhance understanding of this material as needed. · Identify and recommend new policy or program initiatives in the specialty area designed to enhance delivery and quality of service. Program
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requirement, no more than one weekend per month. JOB ELIGIBILITY REQUIREMENTS Work requires graduation from an accredited Associate's Degree in Nursing or Nursing Diploma program. All registered nurses without
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Oversee corporate card (P-card) transactions and monthly reconciliations in Concur. Process reimbursements and travel expenses for faculty, staff, and students. Monitor unassigned expense transactions and
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: Work requires graduation from an accredited Associate's Degree in Nursing or Nursing Diploma program. All registered nurses without a Bachelor's degree in Nursing (or higher) are encouraged to enroll in
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research focuses on developing and applying computational frameworks—including machine learning, nonlinear dynamical systems, and hybrid physics-integrated machine learning models—to predict, analyze