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to the delivery of online programs. Evaluate, test, and implement technology and resources to support program delivery. Support the design and development of courses and programs in collaboration with team members
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Athletics is the largest NCAA Division I athletics program in New York City and the only NCAA Division I sports program in Manhattan. A beautiful and peaceful campus in the heart of New York City, Columbia
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structure and mechanics, and related fields. We are interested in candidates with expertise in observational and/or computational seismology, geodesy, and/or geology. Researchers that utilize AI/ML
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of patients being evaluated and treated by the liver and intestinal program. Conduct new evaluations and consultations. Provide education about liver disease and transplantation for patients and medical center
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never been so inviting! We are currently recruiting a Family Nurse Practitioner to lead and teach in the Family Nurse Practitioner specialty DNP program as well as serve as the Program Director. The
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, and experience. Excellent oral/written communication, interpersonal, organizational, and computer skills (Microsoft Office). Ability to work effectively independently and collaboratively with diverse
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Qualifications Excellent interpersonal and organizational skills. Computer Skills: proficiency with MS Word programs and familiarity with Mac and PC platforms. Clinical research experience or oncology nursing
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. Experience in cardiology, advanced heart failure or transplant a plus. Previous NP experience a plus. Other Requirements Familiarity and proficiency with computer-based programs such as electronic medical
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experiences and strong communication skills. Preferred Qualifications: Excellent teaching records in introductory courses in statistics, probability, machine learning, statistical computing, and data science
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for Computational Electrochemistry (CCCE) is seeking an Associate Research Scientist (ARS) with expertise in surface science, electrochemistry, first-principles electronic structure methods, and machine learning