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the university level, especially in the areas of Business Programing, AI in Business, Business Analytics, Machine learning/Deep Learning, LLMs, Social impact of AI. Experience in teaching Master’s level courses
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the university level, especially in the areas of Business Programing, AI in Business, Business Analytics, Machine learning/Deep Learning, LLMs, Social impact of AI. Experience in teaching Master’s level courses
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, and soil landscape analysis. The incumbent will apply emerging technologies, AI, machine learning, and digital tools to advance the areas of soil mapping, soil classification, soil morphology, and other
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, soil genesis and morphology, and soil landscape analysis. The incumbent will apply emerging technologies, AI, machine learning, and digital tools to advance the areas of soil mapping, soil classification
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from all subfields of condensed matter theory, including those that utilize machine learning and AI in their research, are encouraged to apply, but preference will be given to applicants that have strong
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applicants. Candidates from all subfields of condensed matter theory, including those that utilize machine learning and AI in their research, are encouraged to apply, but preference will be given to applicants
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, faculty, and students. Monitoring computer labs. MacOS, Windows and Linux. Learning IT management tools such as Active Directory, Citrix, Entra, Intune, MCM, VMWare, PVS Tracking and coordinating work using
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to enhancing student success by engaging students in quality academic, research, internships, global studies, and other experiential learning opportunities. There is an expectation that, as part of your role in
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Science (CBEE), within the College of Engineering, invites applications for 9-month, part-time (varied FTE), fixed-term, non-tenure-track, E-campus instructors to teach on a term-by-term basis for the 2025/2026
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Science (EECS), within the College of Engineering, invites applications for 9-month, part-time (varied FTE), fixed-term, non-tenure-track, E-campus instructors to teach on a term-by-term basis for the 2025/2026