Lecturer and/or Course Designer, Integrate Artificial Intelligence and Machine Learning into Information Technology and Cloud Computing Certificates
Role details
Job location
Tech stack
Job description
The School of Continuing and Professional Studies (SCPS),University of Virginia (UVA)seeks applications for one or more non-tenure track, part-time (faculty wage) lecturer position(s) to support theinstructional design, (re)development,and delivery of courses in artificial intelligence (AI), machine learning (ML), and applied cloud-based AI technologies as part ofCloud Computing Undergraduate Certificate, Information Technology Undergraduate Certificate, and forthcomingAIand ML coursework.
SCPS is hiring multiple positions toassistin updating existing courses andtodevelop new courses, with special attention toaddressing AI- and ML-related learning outcomes.All courses are delivered in online three-credit courses at either the undergraduate or graduate level.
Responsibilities may includereviewing and updating learning outcomes,aligningandbuildingrefreshed or newcourse content,developingassignments andassessments,supporting hands-on labs, and teaching or co-teaching liveonline undergraduate and/or graduate course sessions. For lecturer teaching assignments, the ability to lead engaging, interactive sessions online (primarily on Zoom) and in person is essential., The University will perform background checks on all new hires prior to employment. This position will also requireeducationalverification.
The job may occasionally require traveling some distance to attend meetings and programs., Wage Faculty and all personnel actions associated with them are governed and approved by the EVPP and policyPROV-026: Faculty Wage Employment. Faculty wage appointments are subject to change and carry no expectation of renewal from year to year.
Faculty wage employment is usually less than 0.5 FTE (teaching fewer than 6 credits or the equivalent of no more than 19 hours per week); is offered for only one or two semesters at a time; and applies to faculty members paid solely via Period Activity Pay. Wage Faculty (Adjunct) positions are at-will and come with no expectation of renewal, and are not eligible for leave or other benefits.
Because of the significant disciplinary differences between schools, specific employment expectations vary by school and are described in local school policies. Schools may have additional expectations of Wage Faculty who have other documented responsibilities.
Physical requirements of faculty will vary, but may include some or all of the following: traveling to and from work location, other UVA or UVA Health facilities, or to other locations in the U.S. or abroad for meetings or research; using computers, specialized equipment, and other technologies; remaining stationary, moving, bending, lifting, and reaching; performing procedures using fine motor skills; communicating effectively, in writing, in person, in the classroom, online, and in clinical settings; and interacting with others such as colleagues, other academic and medical peers, students, patients, and the public.
Requirements
- Agraduatedegree(master's degree or higher)in computer science, engineering, data science, information systems, or a closely related field isrequired., * Relevant AI, ML, data science, or cloudcertifications(e.g., AWS, Azure, Google Cloud, or equivalent) are preferred., * At least three (3) years of professional experience in artificial intelligence, machine learning, datascience, or cloud-based analytics. This includes experience building, deploying, or working with AI/ML models, tools, or workflows.
- At least two (2) years reaching, training, mentoring, or instructional support experience in technical or professional education settings. This may include experience teaching AI, ML, datascience, or cloud computing in higher education, professional education, or corporate training environments.
Preferred:
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Demonstrated willingness to stay current with emerging AI technologies, tools, and teaching strategies.
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Experience designing hands-on labs, projects, or case studies using platforms such as AWS, Microsoft Azure, Google Cloud, or open-source ML frameworks.
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Experience with online and/or in-person intensive training or education programs.
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Proficiencyusing Canvas or similar learning management systems.
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Relevant industry certifications and/or professional memberships.