513 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at University of Texas Rio Grande Valley
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. Open Date Special Instructions to Applicants All applications must be submitted via the UTRGV application portal at http://careers.utrgv.edu. If you are applying for the first time, please complete all
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to Applicants All applications must be submitted via the UTRGV application portal at http://careers.utrgv.edu. If you are applying for the first time, please complete all biographical information including
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for employment positions of interest. Open Date 01/08/2026 Special Instructions to Applicants All applications must be submitted via the UTRGV application portal at https://careers.utrgv.edu. If you are applying
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for employment positions of interest. Open Date 01/14/2026 Special Instructions to Applicants All applications must be submitted via the UTRGV application portal at https://careers.utrgv.edu. If you are applying
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Posting Details Title Information Faculty Title Job Class Code FLSA Position Information Posting Number FRGV1896 Working Title Lecturer I (Open Rank) - Electrical & Computer Engineering Number
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manages reservations and room/events for program activities, such as meetings, orientations, and professional learning events related to Early Field program goals; drafts agendas, correspondence, and
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at the University of Texas Rio Grande Valley (UTRGV) http://www.utrgv.edu/rcvcobe invites applications for the position of Assistant, Associate or Full Professor of Practice. About UTRGV: It is UTRGV’s Vision “To be
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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, spreadsheet, and database software
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activity submit a summary of the research activity at the end of each semester. Discipline Specific Required Qualifications Health care related background Knowledge of searching databases Computer knowledge
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and