10 machine-learning "https:" "https:" "https:" "https:" "U.S" uni jobs at University of California, Merced
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applications and consultations • Creates outreach and informational materials about the GIS Center including printed flyers and digital graphics Instruction and Learning Support • Provides on-call support in
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the School of Engineering anticipates hiring multiple instructional learning assistants/remedial tutors for the following courses for Academic Year 2025-2026: CSE 005: Intro Computer Applications CSE 015
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Other courses as needed See catalog for course descriptions: https://catalog.ucmerced.edu/content.php?catoid=21&navoid=1993 A Learning Assistant works with groups of students on challenging course
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Machines EE 150: Digital Communication Other courses as needed See catalog for course descriptions: https://catalog.ucmerced.edu/content.php?catoid=21&navoid=1993 A Learning Assistant works with groups
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and sustainable infrastructure that evolves with the research and learning enterprise. The full university strategic plan can be found here: https://strategicplan.ucmerced.edu . Role of the Dean
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Systems CSE 120: Software Engineering CSE 160: Computer Networks CSE 168: Distributed Software Systems CSE 176: Introduction to Machine Learning CSE 180: Introduction to Robotics CSE 185: Introduction
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to Machine Learning CSE 180: Introduction to Robotics CSE 185: Introduction to Computer Vision Other courses as needed See catalog for course descriptions: https://catalog.ucmerced.edu/content.php?catoid=21
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of Engineering anticipates hiring full and/or part-time lecturer positions to teach the following courses for Academic Year 2025-2026: EE 021: Introduction to Electrical Engineering Programming EE 060: Boolean
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filled. Position description The Mechanical Engineering department in the School of Engineering anticipates hiring full and/or part-time lecturer positions to teach the following courses for Academic Year
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sensing image processing, and leverage R and Python for statistical analysis. You will also contribute to machine learning-based and hydrologic modeling to derive meaningful insights from environmental data