96 parallel-computing-numerical-methods positions at University of California, Merced
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The School of Engineering anticipates hiring Teaching Assistants for lower- and upper-division courses for Academic Year 2025-2026, including Summer Session 2025, in the following disciplines: Computer
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of employment (parallel to tenure track). This position will have responsibilities to coordinate and teach undergraduate and graduate courses in all areas of Aerospace Engineering with an anticipated start date
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, as well as parallel and distributed computing. Additionally, the Postdoctoral Scholar will collaborate closely with the PI to produce research articles aimed at disseminating the findings obtained from
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The School of Engineering anticipates hiring Teaching Fellows for lower- and upper-division courses for Academic Year 2025-2026, including Summer Session 2025, in the following disciplines: Computer
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description The Teacher Preparation Program in UC Merced Extension Education Programs invites qualified applicants to apply for the University Mentors of Teacher Candidates position for the academic year 2024
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Position overview Position title: Instructor, Teacher Preparation Program Salary range: An estimated range for this position is $1,875 to $4,500 per course. Anticipated start: As early as August
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Position overview Position title: Part-Time Program Coordinator Salary range: Up to 20% time of Step I. See Table 36 for the salary range for this position. The expected compensation
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date will only be considered if the position has not yet been filled. Position description Special topics covered in undergraduate studies. Learn more about what to expect from CORE program. The CORE
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on advancing agricultural food technology through the integration of artificial intelligence (AI). Specifically, the Postdoctoral Scholar is expected to conduct intellectual research involving parallel and
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. Preferred qualifications Experience with differential equations and related numerical methods. Experience with programming pipelines for training, validation, and inference of machine learning models in