418 machine-learning-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at Virginia Tech
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Job Description The Learning Specialist will work with colleagues in Student Athlete Academic Support Services (SAASS) to meet the academic support needs of student-athletes. Specifically
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Job Description The Instructional Designer will collaborate with faculty and subject matter experts to design, develop, and deliver engaging, accessible, and innovative courses and learning
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the future of computing at Virginia Tech through research, teaching, and service. The candidate will teach core courses in computer engineering—such as embedded systems, computer architecture, and network
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, organizational and time management skills with ability to execute program plans • Proficient computer skills such as email tools, data entry, and manipulating Excel spreadsheets • High comfort level with learning
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. • Proficient communication skills. • Track record of conducting original research and publishing in peer-reviewed scientific journals. Preferred Qualifications • Experience in remote sensing or machine learning
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• Interest in continuous learning Overtime Status Exempt: Not eligible for overtime Appointment Type Restricted Salary Information Commensurate with Experience with a minimum of $50,000 Hours per week 40
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reading. In Virginia Tech’s Division of Student Affairs, that’s exactly what we do every day—guiding, nurturing, and supporting students as they learn and grow into the leaders and world-changers of today
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Qualifications Bachelor’s degree or equivalent combination of education and experience; Knowledge of advanced accounting principles and practices; Capacity to learn and flow University financial policies and
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administrative support to multiple senior or executive level leaders. Familiarity with university policies and procedures. Experience collecting data and/or managing databases. Demonstrated ability to learn
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. Responsibilities: • Design and conduct experimental research on paper-based materials for food packaging applications. • Develop predictive models for packaging performance using machine learning and physicochemical