506 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" positions at University of Texas Rio Grande Valley
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. Provides operational and documentation support for assurance-of-learning and accreditation activities, including AACSB reporting and maintenance of required records. Maintains frequent interaction with
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plan, vision, mission, values and core priorities (https://www.utrgv.edu/strategic-plan/ ). About UTRGV: UTRGV serves the Rio Grande Valley and beyond via an innovative and unique multicultural education
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Computer Engineering Division Provost - Academic Affairs FTE .5 Scope of Job Maximum appointment is limited to twenty (20) hours per week (50% FTE) during the Fall and Spring semesters. Maximum appointment
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medical school is preferred. The chosen individual will assist in implementing a vertically and horizontally integrated curriculum utilizing active, team based, and problem based learning, flipped classroom
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research spanning theoretical foundations, bioinformatics, machine learning, robotics, data mining, and applications of Computer Science. Together, the programs prepare students for graduate study in
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of Job To support the operation, coordination, and execution of Career Center programs and initiatives, including career readiness, employer engagement, and experiential learning efforts. Responsible
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Tenure Status Non Tenure Track FTE 1.0 Scope of Job The School of Art and Design at The University of Texas Rio Grande Valley (UTRGV) is hiring One (1) one-year lecturer to start Fall 2025 to teach in its
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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
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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