516 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" positions at University of Texas Rio Grande Valley
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Equipment Use of standard office equipment, personal computer, and audio/visual equipment. Working Conditions Needs to be able to successfully perform all required duties. Office Environment; constant travel
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computer, word processing, spreadsheet, and database software. Standard office equipment. Working Conditions Needs to be able to successfully perform all required duties. Work is performed primarily in a
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faculty and staff that can contribute to an enriching learning environment that strives for more equitable outcomes for student success. UTRGV is a distributed campus, one university spanning four counties
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of Job The Department of Organization & School Leadership at The University of Texas Rio Grande Valley (UTRGV) occasionally needs to hire non-tenure track, part-time lecturers to teach the at graduate
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an accredited university. Applicants must have at least 2 years teaching experience, which enables them to teach combinations of molecular/cell biology, biochemistry, neuroscience, cell and molecular biology
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experience, preferably in academic advising, admissions, and/or student recruitment. Equipment Use of standard office equipment. Strong computer skills and knowledge of Microsoft, including but not limited
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experience. Experience may be substituted for education on a 1-on-1 basis Preferred Experience Experience obtained within higher education. Equipment Knowledge of the use of personal computer, word processing
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at https://careers.utrgv.edu for detailed contact information. Additional Information UTRGV is a distributed location institution and working location is subject to change based on need. All UTRGV employees
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or a strong aptitude for using advanced computational tools, AI, or machine learning techniques to address engineering challenges; and interest or initial experience in interdisciplinary collaboration
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journals or conferences; experience with or a strong aptitude for using advanced computational tools, AI, or machine learning techniques to address engineering challenges; and interest or initial experience