221 data-"https:"-"https:"-"https:"-"https:"-"U.S"-"UCL"-"UCL" positions at Virginia Tech
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to recruit, select, train and manage volunteers; demonstrated ability to lead groups, plan, implement, facilitate, teach and evaluate educational information programs; knowledge and use of computer technology
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Status Non-Exempt: Eligible for overtime Appointment Type Regular Salary Information $46,000-$48,000k Hours per week 40 Review Date February 2nd, 2026 Additional Information The successful candidate will
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Appointment Type Regular Salary Information $44,000 - $47,000 Hours per week 40 Review Date 01/07/2026 Additional Information The successful candidate will be required to have a criminal conviction check. About
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at the AREC. • Computer skills of the level necessary to facilitate record keeping and data management as required for management of the research farm. • Must have a valid driver's license, good driving record
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, fluorescence in situ hybridization, and bioinformatics. Preferred Qualifications Molecular biology and genetics laboratory experience; web computer skills; ability to learn new techniques and procedures
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: Not eligible for overtime Appointment Type Regular Salary Information Commensurate with experience Hours per week 40 hours - exempt position Review Date January 9, 2026 Additional Information
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or strong interest in developing knowledge of one or more humanities fields Pay Band 2 Overtime Status Non-Exempt: Eligible for overtime Appointment Type Restricted Salary Information Commensurate with
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Job Description The Virginia Tech Institute for Advanced Computing (IAC), in partnership with the Departments of Computer Science (CS) and Electrical and Computer Engineering (ECE), invites
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field of artificial intelligence and its implications on news, information, and democracy. We seek candidates with demonstrated scholarly achievement, or potential for such achievement, aligned with
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systems. The individual will be responsible for: • Develop and implement models for the structural and mechanical performance and optimization of mass timber systems, using data-driven approaches