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candidate must hold a terminal degree (PhD or MFA). Candidates should have previous teaching experience and a proven ability to mentor students effectively. Preferred qualifications include familiarity with
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. Machine Learning and Programming 4. Cloud Computing. Desirable education and experience: A Ph.D. in Information Systems, Analytics, Decision Sciences, or a related field from an AACSB-accredited business
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for a public or technical service unit in the University Library System. Work activities necessitate proficiency in library methods and procedures and the ability to utilize on-line computer systems and
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foundational to complex systems modeling and central to modern machine learning. Candidates whose research includes computational components or contributes to the mathematical foundations of artificial
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technologies (machine learnings and Artificial Intelligence) into the classroom and research are encouraged to apply. Candidates should be able to teach face-to-face, hybrid, and/or online courses in
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experiential learning. Research on topics including Indigenous rights, African diaspora, or environmental anthropology would especially complement departmental foci. Experience working in cultural resource
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the implementation of artificial intelligence and machine learning in design and manufacturing, materials informatics and big data design, smart manufacturing, characterization and processing of materials, scalable
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foundational to complex systems modeling and central to modern machine learning. Candidates whose research includes computational components or contributes to the mathematical foundations of artificial
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Analytics and Data Sciences (Analytics, Artificial Intelligence (AI)/Machine Learning (ML), Quantum Computing, Natural Language Processing (NLP), Technical MIS courses) · Cybersecurity (Network
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technologies (machine learnings and Artificial Intelligence) into the classroom and research are encouraged to apply. Candidates should be able to teach face-to-face, hybrid, and/or online courses in