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The Rutgers School of Nursing is seeking full time faculty qualified to teach clinical, laboratory, and simulation courses in our newly established Division of Simulation and Clinical Learning. In this role
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innovation (eg, multi-omics, machine learning, remote assessment), and enthusiasm for team science and collaboration. Faculty will work collaboratively with CHA, IFH and Rutgers leadership to develop signature
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clinically relevant basic science content in pre-clerkship courses, with a particular focus in neuroscience or gross anatomy and histology. Responsibilities will include coordinating small-group learning
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will teach and develop courses at the intersection of science, technology, and business—such as intellectual property management, and related areas. The role also emphasizes external engagement, and
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the possibility of renewal based on performance and continued funding. The position carries a 3–1–3 teaching load (spring, summer, fall). The successful candidate will teach core and elective courses in accounting
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the Division of Student Academic Success, comprised of the Vice Chancellor for Student Academic Success, Office of Retention, Center for Learning and Student Success, Educational Opportunity Fund (EOF), TRIO
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savings options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu
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leader in the delivery of effective, compassionate and accessible care informed by research within correctional environments. We Care. We Teach. We Heal. We Improve. Rutgers, The State University of New
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power supply. Candidates with relevant expertise in renewable energy, wind turbines, solar power, computational and structural mechanics, artificial intelligence and cybersecurity, machine learning, data
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power supply. Candidates with relevant expertise in renewable energy, wind turbines, solar power, computational and structural mechanics, artificial intelligence and cybersecurity, machine learning, data