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Schiller International University · 12 hours ago

Adjunct Instructor in Computer Science and Data Science (Immediate Appointment) - Tampa

Tampa, FL

Part-time

Onsite

Mid, Senior Level

3+ years exp

Schiller International University is seeking visionary PhD holders and MSc scholars in Computer Science and Data Science to join their faculty. The instructor will lead an Immersive Technology Lab and engage students in hands-on, real-world projects while promoting the university’s vision of training future-ready graduates.

Higher Education

Responsibilities

Demonstrate leadership to students in immersive, hands-on lab work and engage students in real-world, integrative projects

Promote the university’s vision, to training international future-ready graduates with cutting-edge immersive technologies in STEM and other disciplines

Organize seminars, hackathons, coding festivals and networking events for students to connect directly with industry, colleagues and peers

Responds to student inquiries in a timely manner, facilitating discussions and relevant guidance in accordance with university policy, utilizing university assigned email account

Maintain announcement and communication schedule in each course in a timely manner

Grade and assess student work using approved rubrics, ensuring fairness and accuracy

Provide timely and constructive feedback on summative and formative assessments to students via Blackboard with clear explanation to grading

Address academic concerns such as academic integrity issues, grade disputes, and challenges within established timelines

Monitor student progress through our learning management software (Blackboard) tools, identify at-risk students, and collaborate with our academic advisor and the Associate Dean of STEM to provide support for successful course completion

Fulfill academic and administrative duties, including documentation, compliance with policies, and participation in faculty meetings and training as well as promoting constructive collaboration with colleagues

Promote integrity and professionalism by adhering to Schiller International University policies, handbooks, and accreditation requirements

Provide support to innovation by sharing ideas on good practices, integrating e-books and digital tools into student engagement strategies

Other responsibilities as assigned by the Associate Dean of STEM, Chief Academic Officer / Provost and/or Campus Director

Qualification

PhD in Computer ScienceProgramming pedagogyMachine learningImmersive technologyHands-on teachingLMS (Blackboard)Industry collaborationStudent-centered approachVirtual laboratory experienceEnglish proficiency

Required

Terminal degree (PhD) in Computer Science, Applied Mathematics, Artificial Intelligence, Human-Computer Interaction, or related fields

Experienced in Programming pedagogy, machine learning, robotics, immersive technology

Expertise in hands-on teaching in a virtual laboratory, industry collaboration, and ideally some published work in immersive technologies

Innovative, student-centered, and comfortable bridging academia and applied industry skills

Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or governmental regulations

Ability to write reports, business correspondence, and procedure manuals

Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the public

Preferred

3-5 years of professional experience at university level teaching preferred

Practical experience with LMS (Blackboard) or comparable e-learning tools

Industry experts and professionals with PhDs and interested in academia are encouraged to apply

Postdoctoral candidates and recent postdocs working in immersive computing and AI research groups are encouraged to apply

Candidates able to teach the following courses are invited to apply as soon as possible: Data Structures and Algorithms, IT Project Management, Computer Networking, Mobile Application, Digital Analytics, Statistics and College Algebra