Adjunct Instructor- Artificial Intelligence- CTU Online

Position Description Consistent with and supportive of CTU's mission (to provide industry-relevant higher education to a diverse student population through innovative technology and experienced faculty, enabling the pursuit of personal and professional goals), Adjunct Faculty members provide quality and innovative instruction and meaningful engagement with our students to successfully achieve the relevant course, program, and degree level outcomes and support their academic success. Responsibilities Prepare relevant, insightful, and engaging instructional materials and utilize existing course materials that support learning by CTU's student population. Provide instruction in assigned courses (including applicable laboratory or work that is integral to the courses) that aligns with CTU's curricula and outcomes, instructional modalities, course technologies, and faculty expectations. Engage and communicate with students to encourage their course participation and learning while maintaining mutual respect and professionalism. Relate professional/industry experience to CTU's Professional Learning Model by the continuation of professional/technical skills development, introduction of professional/industry perspectives into courses, and active awareness of professional/industry trends and opportunities. Maintain accessibility for and provide timely responsiveness to students, academic/faculty leadership, and University staff by telephone, CTU e-mail, and other appropriate means of communication. Establish and maintain weekly office hours for student questions/support. Assess student performance on course assignments and provide assignment feedback to support continued student growth and development. Maintain appropriate documentation of student course activities. Work with appropriate CTU teams (e.g., advising, academic/faculty leadership, and University staff) and leverage appropriate information to identify and support students who may be exceptional or challenged in their coursework and/or educational endeavors. Refer students to appropriate co-curricular and extra-curricular resources (e.g., advising, tutoring, library, learning centers, and career services). Participate in and contribute to CTU's academic governance through attendance at appropriate University/college/program meetings and participation in the academic assessment and institutional effectiveness process (including completion of appropriate surveys and participation in continuous improvement initiatives). Successfully complete required new faculty certification training, course-specific technology/pedagogical training, annual ethics and information technology policy training, and annual faculty development requirements. Provide periodic required documentation of ongoing and updated licensures, certifications, immunizations (as appropriate to the specific college/program), scholarship, and academic/professional experience (e.g., CVs/resumes). Work closely with Program Chair and/or Lead Faculty (as appropriate). Perform other responsibilities and abide by the appropriate policies and procedures contained in CTU's Faculty Handbook. Required Skills Strong organizational and time management skills, with proficiency in meeting deadlines and urgency in responding to questions/requests. Strong interpersonal and oral presentation/written communication skills. Proficiency in working effectively, cooperatively, and flexibly in a team environment. Proficiency with standard office and mobile applications (i.e., word processing, presentations, e-mail, calendaring, teleconferencing, text messaging, personal computers, and smart phones/tablets). Required Experience A Master’s or PhD degree in Computer Science, or Electrical Engineering, or Computer Engineering. Deep Knowledge of GPU Architecture: In-depth understanding of GPU architecture, including parallel computing, memory management, and performance optimization. Experience with NVIDIA Technologies: Familiarity with NVIDIA technologies such as CUDA, TensorRT, and other tools and frameworks provided by NVIDIA. Practical experience in the industry, particularly in roles involving GPU programming, AI, and machine learning applications. Previous teaching experience at the university level, especially in courses related to computer architecture, parallel computing, or AI. Strong verbal and written communication skills to effectively convey complex concepts to students. Curriculum Development: Ability to develop and update course materials, including lectures, assignments, and exams, to keep pace with advancements in GPU technology and AI. Research Contributions: Active involvement in research, particularly in areas related to GPU architecture and AI, can be a plus. NVIDIA Certification: Certification from NVIDIA, such as becoming an NVIDIA-Certified Instructor, can be highly beneficial. This certification demonstrates proficiency in NVIDIA technologies and the ability to teach them effectively.