179 machine-learning "https:" "https:" "https:" "https:" "https:" positions at University of Texas Rio Grande Valley
Sort by
Refine Your Search
-
Listed
-
Field
-
of under-represented groups; will demonstrate through their research, teaching, and/or public engagement the richness of diversity in the learning experience; will integrate multicultural experiences
-
potential for using technology effectively to foster students’ learning and a strong commitment to inclusive teaching practices. · Demonstrated proficiency in written and oral use of the English language
-
Intelligence (AI)/Machine Learning. Successful candidates will contribute to one or more of the research centers in the College of Engineering & Computer Science and in particular to the University
-
the discipline of Cell Biology and/or Pathology. The chosen individuals will assist in implementing a vertically and horizontally integrated curriculum utilizing active, team-based and problem based learning
-
or revising curriculum: ASL, and interpreting. Experience with visual pedagogy and designing inclusive, accessible learning environments for diverse learners. Familiarity with online or hybrid ASL instruction
-
Posting Details Position Information Posting Number SRGV8577 Working Title LEARNING INSTRUCTIONAL SPECIALIST I Number of Vacancies 1 Location Brownsville, Texas Department College Access & K-12
-
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
-
developmental and introductory courses in mathematics and statistics to more than 10,000 students each semester across hundreds of course sections. Please visit the SMSS webpage at www.utrgv.edu/math to learn
-
developmental and introductory courses in mathematics and statistics to more than 10,000 students each semester across hundreds of course sections. Please visit the SMSS webpage at www.utrgv.edu/math to learn
-
the participation of all health-related programs and create a stronger framework for collaboration and impact among health-related programs. The goal is for the division to boost interdisciplinary learning, enhance