417 machine-learning "https:" "https:" "https:" "https:" "https:" "Cardiff University" positions at Indiana University
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preferred. Applications, including a CV, a statement of research interests and future plans, and three letters of reference, should be submitted through the application portal located at: https
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) the names and contact information for three letters of references. Application materials may be submitted via (https://indiana.peopleadmin.com/postings/30945 ). Review of applications will begin immediately
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review position requirements and apply at https://indiana.peopleadmin.com/postings/30635 Applications received before January 1, 2026, will be given full consideration; however, applications will be
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candidates should review the application requirements and submit their application at https://indiana.peopleadmin.com/postings/30457 . Applications must be received by September 26, 2025, to be assured of full
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seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join
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research o Experience analyzing intensive longitudinal data (e.g., EMA) The anticipated start date is Fall 2026. Start date is negotiable. Interested individuals should apply at https
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for three references to https://indiana.peopleadmin.com/postings/32142 Letters of reference will be requested from candidates who are selected for further consideration. Basic Qualifications The successful
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research agenda using advanced quantitative methods—such as machine learning, computational modeling, big-data analytics, and wearable technologies—to study tourism, hospitality, and/or human performance
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, 2) your curriculum vita, and 3) names of at least three references electronically to https://indiana.peopleadmin.com/postings/32305 . We will begin reviewing applications on March 23rd, 2026. Please
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to candidates also holding a master’s degree in a business-related field, a record of excellent teaching, and a commitment to student learning. Preference will be given to candidates with professional work