583 computer-programmer-"the"-"IMPRS-ML"-"IMPRS-ML"-"Prof"-"UNESP" positions at University of Virginia
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Education: Graduate of an accredited graduate school of nursing or physician assistant program with a master’s degree. Experience: Department and unit specific. Licensure: License or license eligible as an
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Retirement through the Virginia Retirement System Tuition and professional development benefits Employee wellness program featuring activities to earn up to $500/year Physical Demands: The employee must be
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, other duties may be assigned. MINIMUM REQUIREMENTS Education: Bachelor of Science in Nursing from accredited nursing program, Master's degree in related field within 5 years of hire. Experience: At least
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studies needed to advance the missions of our research program. This is a leadership position within the lab, and the successful candidate will serve as the principal investigator's scientific partner
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considering past requirements, expenditures, and current program plans. Managing grant submissions. Compiling reports and analyses, noting progress and/or adverse trends and recommending solutions. Serving
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REQUIREMENTS Education: Graduate of an accredited nursing program required. Bachelor of Science in Nursing required within 5 years of hire. Experience: 1 year of relevant experience. Licensure: Licensed
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required. Certified to practice as a Nurse Aide in the Commonwealth of Virginia OR must meet one of the following criteria (required): (1) Successful completion of the UVa PCT Education Program OR
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to meet healthcare and financial needs Retirement through the Virginia Retirement System Tuition and professional development benefits Employee wellness program featuring activities to earn up to $500/year
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the Virginia Retirement System Tuition and professional development benefits Employee wellness program featuring activities to earn up to $500/year Selected candidates will be required to complete all required
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of bioinformatics and computational biology. The lab’s research program focuses on developing computational methods for high-throughput genomics technologies and integrating data science and experimental approaches