524 parallel-and-distributed-computing uni jobs at Cornell University in United States
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influential tech roles—enabling them to write the rules that will shape the future of all of us. Break Through Tech’s AI Studio program is an innovative work-embedded learning program that matches undergraduate
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work under pressure, and solid internet/computer skills. Ability to work in teams demonstrated by cooperation, respect, and flexibility with other coworkers. Ability to advocate for individuals from a
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top-tier law school. We offer a 3-year JD program for about 200 students per class, a one-year LLM program for about 90 students from countries throughout the world, and a doctoral (JSD) program for
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audio-visual support in classrooms and conference rooms as well as end-user support and maintenance for our desktop computing environments. This role will be primarily based at our Breazzano Family Center
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supervision including but not limited to dealing with camper behavior issues, failure to thrive in camp environment, etc., assisting with weekly program design, implementing afternoon and evening programs and
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(50%) and teaching (50%) on a 9-month academic year basis. Research (50%): The successful candidate will be expected to conduct an internationally recognized and externally funded research program to
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-day administrative and organizational support for the LAG team. Support the planning and execution of a premier alumni volunteer solicitation program. Assist in the coordination of communications
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at Cornell . Cornell's impressive educational benefits include tuition-free Extramural Study and Employee Degree Program, tuition aid for external education, and Cornell Children's Tuition Assistance Program
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at Cornell Cornell's impressive educational benefits include tuition-free Extramural Study and Employee Degree Program, tuition aid for external education, and Cornell Children's Tuition Assistance Program
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variety of genetic, molecular and cell biology techniques, including cloning, protein biochemistry, structural biology, computer programming, machine learning, tissue culture, fluorescence imaging, genetic