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Machining and Integration Specialist - Job Number: 251658 Organization : Aerospace & Mechanical Engin. Job Location : Oklahoma-Norman-Norman Campus Schedule : Full-time Work Schedule: Monday
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to teach one or more of the courses in programming, data communications, computer networking, database management, cybersecurity, and other related areas in computer information systems or Computer Science
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funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals (33%) • Conduct full stack development
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to the campus department instructional leader, adjunct instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and educational
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instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and educational technologies available to complement the teaching and
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department instructional leader, adjunct instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and educational technologies
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Research experience and publication records in Computational Mathematics, Scientific Machine Learning, Mathematics Modeling, Artificial Intelligence, Data Science, High-Performance Computing, or Optimization
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be prepared to teach a range of courses within the Machine Shop - CNC (Industrial Technology) discipline, promoting engaging and inclusive educational environments that support student learning
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department instructional leader, adjunct instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and educational technologies
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to the campus department instructional leader, adjunct instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and educational