588 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Cornell University in United States
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our benefits: https://hr.cornell.edu/benefits-pay . Follow this link to learn more about the Total Rewards of Working at Cornell: https://hr.cornell.edu/jobs/your-total-rewards . Our leave provisions
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about our benefits: https://hr.cornell.edu/benefits-pay . Follow this link to learn more about the Total Rewards of Working at Cornell: https://hr.cornell.edu/jobs/your-total-rewards . Our leave
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applications for an Assistant Teaching Professor position in the School of Electrical and Computer Engineering. The successful candidate will be expected to teach courses primarily in computer engineering
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an appointment through December 31, 2026. More information about the ILR School can be obtained at our web site, http://www.ilr.cornell.edu and the Yang-Tan Institute at http://www.yti.cornell.edu/ . We require
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to apply and submit all required application materials (see list below): https://academicjobsonline.org/ajo/jobs/31185 Review of applicants will begin as soon as December 1, 2025, and will continue until
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machine learning and network biology. Background in cancer research. Pay Range: $62,232.00 - $81,000.00 To apply visit https://academicjobsonline.org/ajo/jobs/31509 and submit a cover letter, full CV, and
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home will be the Nolan School, but it is expected that faculty teach across the three schools within the College of Business. The Cornell Peter and Stephanie Nolan School of Hotel Administration is the
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implementation. Anticipated Division of Time Program Leadership and Development: Lead the planning, development and implementation of Precision Dairy Nutrition, teach nutritionists and dairy farmers to develop and
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systems, data science, business analytics, and machine learning; supervision of doctoral students; and service to the academic community, the OTIM area, the SC Johnson College of Business, and the
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. The focus of this position is developing methods to disentangle dynamic, multiscale ecological signals from large, noisy observational data. This work lies at the interface of statistics, machine learning/AI