841 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " positions at Cornell University
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responsibilities for academic and nonacademic positions within the department. To apply: Please apply via Academic Jobs Online https://academicjobsonline.org/ajo/jobs/31846 Qualified candidates should submit a short
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: http://cce.cornell.edu/sites/default/files/applying_external.pdf. Internal Applicants: Current employees of Cornell Cooperative Extension of Ontario County are considered internal applicants. Please log
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responsibility for teaching in the veterinary curriculum, including facilitating problem-based learning groups in the pre-clinical physiology curriculum (approximately 12 weeks of teaching commitment), and
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learning, intellectual engagement, and hands-on experience with a wide array of cutting-edge techniques in genomics, metabolomics, and microbial research – all within a collaborative and inclusive scientific
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should submit materials to CornellVPandGC@SpencerStuart.com . For additional information about Cornell University, please visit https://www.cornell.edu/ . The Opportunity The Vice President and General
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diverse team and perform with minimum supervision. Have basic computer and technical skills including familiarity with Microsoft Office and the ability to learn electronic medical record system (ezyVet)and
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on the NRSA stipend levels. Applications must be submitted through Academic Jobs Online: https://academicjobsonline.org/ajo/jobs/31543 We will begin reviewing applications immediately and will continue until
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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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information. Ability to work effectively with college, university, and departmental financial offices. Commitment to continuous learning. Preferred Qualifications Experience in higher education with grant
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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