UDST
The primary responsibility of faculty members at the College of Computing and IT is to foster high-quality applied learning, innovative research, and service. Additionally, faculty are expected to collaborate with college management and other faculty members to fulfill the college’s mission, deliver academic programs, conduct research, and participate in various administrative and academic services.
Reporting to the Department Head, the successful candidate will be tasked with the development, delivery, and assessment of a diverse range of courses in Data Science and Artificial Intelligence. Key areas of focus include Machine Learning, Deep Learning, Visualization and Intelligent Interaction, Industrial and Business Analytics, IoT Software and Systems, and IoT Intelligence and Automation. Candidates with strong expertise in other related areas of Data Science and Artificial Intelligence will also be considered. Additional responsibilities include evaluating student progress and managing resources within the learning environment. The successful candidate will work closely with industry and other educational institutions, participate in industry advisory committees, and coordinate, manage, and oversee projects within the designated program area. Faculty members are expected to maintain course portfolio documents necessary for accreditation processes and engage in instructional development and improvement initiatives. All faculty are encouraged to contribute to the professional and community life of the university and beyond.
Skills and Qualifications
Faculty members will be appointed at the appropriate rank based on their education and experience (both academic and/or industry). Below are the broad criteria.
Education
A Ph.D. and a Master’s degree in Data Science and Artificial Intelligence or a closely related field from a recognized international university, along with an undergraduate degree from an accredited institution.
For Assistant Professor:
Experience
- A minimum of 3 years of teaching experience in a post-secondary, adult training, or industry training environment, along with preferably 3 years of professional experience in the relevant field.
- An active research agenda demonstrated by high-quality publications in top-tier journals and conference proceedings.
- Proven leadership in fostering engagement and partnerships with the profession and industry.
Preferred Qualifications
- Professional certification in Data Science and Artificial Intelligence.
- A diploma in Education (e.g., Post-secondary Education, Adult Education, and Vocational Education) is preferred.
- Over 6 years of professional experience in the relevant discipline.
- Experience in leadership and innovation in technology-based projects
For Associate Professor:
Experience
- At least 8 years of teaching experience in a post-secondary, adult training, or industry training environment, along with preferably 3 years of professional experience in the relevant field.
- A distinguished research record and international reputation evidenced by high-quality publications in predominantly top-tier journals.
- A strong track record of supervising research students.
- Demonstrated leadership in fostering engagement and partnerships with the profession and industry.
Preferred Qualifications
- Professional certification in Data Science and Artificial Intelligence.
- A diploma in Education (e.g., Post-secondary Education, Adult Education, and Vocational Education) is preferred.
- Over 10 years of professional experience in the relevant discipline.
- Teaching experience in post-secondary, adult training, or industry training environments.
- Experience in leadership and innovation in technology-based projects.
Other Required Skills:
- Comprehensive knowledge and work experience in Machine Learning, Deep Learning, Natural Language Processing, Statistical Learning and Modeling, and IoT applications. Candidates with strong expertise in other areas of Data Science and Artificial Intelligence will also be considered.
- Commitment to applied and experiential learning as a pedagogical approach, aligning with UDST’s mandate.
- Ability to design, develop, deliver, and assess authentic learning experiences and evaluations, incorporating contemporary tools and resources to maximize content learning in context, as well as develop the knowledge, skills, competencies, and attitudes outlined in program outcomes.
- Digital literacy and proficiency in technology systems, with the capability to model and facilitate the use of current and emerging digital tools to support research and learning.
- Demonstrated ability to create technology-enriched learning environments that empower students to actively engage in their learning.
- Commitment to the effectiveness, vitality, and self-renewal of the teaching profession through self-directed continuous professional development and lifelong learning.
- Strong oral and written communication skills.
- A collaborative and collegial spirit, with a proven ability to establish rapport with learners, colleagues, sponsor-employers, and community members.
- Ability to initiate applied research projects.