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Two Faculty Positions Available in the Department of Statistics and Data Science, Cornell University
these two positions reside, the Cornell Ann S. Bowers College of Computing and Information Science , and the School of Industrial and Labor Relations (ILR). Specializations in the department range from
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notifications June 1 - September 1, 2026: Fellowships start Program Details and Benefits Eligibility Requirements Applicants must have received their Ph.D. in a field relevant to the proposed research by
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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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around the world. Position Function The Department of Earth and Atmospheric Sciences at Cornell University is seeking a Senior Research Associate to lead an innovative research program in AI, Deep Learning
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innovative research program in AI, Deep Learning, and machine learning applications for climate science. This research position will advance cutting-edge approaches to climate prediction, extreme event
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or equivalent combination Strong background in computing science and physics Ability to cultivate and develop inclusive working relationships with students, faculty, staff, and community members. Familiarity with
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Qualifications: ● PhD in experimental high-energy physics is required by the start of the appointment ● Strong record of accomplishment in data analysis ● Experience or interest in detector work or detector
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13 additional holiday days with generous holiday pay if you work on those days An award-winning employer provided benefits program Comprehensive health care options Access to wellness programs Employee
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Government Project Attorney - Cornell Law School Founded in 1887, Cornell Law School is a 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
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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