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

We invite visionary PhD holders and MSc scholars in Mathematical Statistics, Financial Mathematics, Data Science, with practical teaching experience to join us at Schiller International University in shaping the future of experiential and project-based education. The instructor will have the opportunity not only to teach but also to lead a state-of-the-art Immersive Technology Lab, fostering collaboration among students, colleagues, industry partners, and researchers to redefine the engagement of Data Science, Computer Science and their applications.

• Demonstrate leadership to students in immersive, hands-on statistical tools and engage students in real-world, projects-based learning.
• Promote the university’s vision, to training international future-ready graduates with cutting-edge immersive technologies in STEM and other disciplines.
• Organize seminars 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 credentials.
• 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 students’ 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.

Educational Profile and Experience of Ideal Candidate

• Terminal degree (PhD) or master’s degree in applied Statistics, Financial Mathematics, Artificial Intelligence, or related fields.
• Experienced in Programming pedagogy, R and Python software, machine learning, and immersive technology.
• Expertise in hands-on teaching in a virtual laboratory, industry collaboration, and ideally some published work in immersive technologies will be an advantage.
• Innovative, student-centered, and comfortable bridging academia and applied industry skills.
• 4-5 years of professional non-teaching industrial experience is preferred (desirable).
• Practical experience with LMS (Blackboard) or comparable e-learning tools (desirable but not a requirement).
• 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.

Language and Communication Skills

Either native English speaker or proficiency level of English competency. 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.

Computer Skills

• Proficiency in Microsoft Office (Word, Excel, PowerPoint, Outlook).
• Experience with Blackboard (Collaborate Ultra) or equivalent LMS preferred.