Responsibilities

Your Commitment

The primary role of the faculty members at the College of Computing and IT is to promote high-quality applied learning, innovative research, and service. Besides, he/she should collaborate with the college management and the rest of faculty to achieve the college's mission, deliver academic programs, pursue research, and engage in several administrative and academic services.

Reporting to the Department Head, the successful candidate will be responsible for the development, delivery and evaluation of a broad range of courses within Data Science and Artificial Intelligence. Particular areas of interest include Machine Learning, Deep Learning, Visualization and Intelligent Interaction, Industrial and Business Analytics, IoT Software and Systems, and IoT Intelligence and Automation, but candidates with strong expertise in other areas related to Data Science and Artificial Intelligence will also be considered. Other duties include evaluation of student progress and management of resources of the learning environment. The successful candidate will liaise with industry and other educational institutions; participate in industry advisory committees and coordinate, manage and control projects within the specified program area. Faculty members will keep course portfolio documents required for accreditation processes and engage in instructional development/improvement plans. All faculty are expected to contribute to professional and community life within the university and beyond.

Skills

Qualifications

Education and Experience Requirements

Faculty members will be placed in the appropriate rank based on their education and experience (academic and/or industry). The broad criteria are provided below.

Education

PhD and a Master's degrees in Data Science and Artificial Intelligence or closely related field from an internationally recognized university with an undergraduate degree from an accredited university.

For Assistant Professor

Experience

• A minimum of 3 years teaching experience in a post-secondary, adult training or industry training environment, along with preferably 3 years of employment experience as a practitioner/professional within the relevant discipline.
• An active research agenda evidenced by high-quality publications in top tier journals and conference proceedings. 
• Demonstrated leadership in building engagement and partnership with the profession and industry.

Preferred Qualifications 

• Professional Certification in Data Science and Artificial Intelligence.
• Diploma in Education (e.g., Post-secondary Education, Adult Education, and Vocational Education) is preferred.
• 6+ years of employment experience as a practitioner/professional within the relevant discipline.
• Experience in leadership and innovation in technology-based projects.

For Associate Professor

Experience

• A minimum of 8 years teaching experience in a post-secondary, adult training or industry training environment, along with preferably 3 years of employment experience as a practitioner/professional within the relevant discipline.
• A distinguished research record and international reputation evidenced by high quality publications in mainly top tier journals. 
• Excellent record of supervising research students.
• Demonstrated leadership in building engagement and partnership with the profession and industry.

Preferred Qualifications 

• Professional Certification in Data Science and Artificial Intelligence.
• Diploma in Education (e.g., Post-secondary Education, Adult Education, and Vocational Education) is preferred.
• 10+ years of employment experience as a practitioner/professional within the relevant discipline.
• Teaching experience in post-secondary, adult training, or industry training environment.
• Experience in leadership and innovation in technology-based projects.

Other Required Skills: 

• A thorough 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 be considered as well.
• Commitment to applied and experiential learning as a pedagogy and a key feature of UDST’s mandate.
• Ability to design, develop, deliver, and evaluate authentic learning experiences and assessments. These should incorporate contemporary tools and resources to maximize content learning in context, and to develop the knowledge, skills, competences and attitudes identified in program outcomes.
• Digital literacy and demonstrated fluency in technology systems, and an ability to model and facilitate use of current and emerging digital tools to support research and learning.
• Demonstrated ability to develop technology-enriched learning environments that enable students to be active participants in their own learning.
• Commitment to the effectiveness, vitality, and self-renewal of the teaching profession through self-driven continuous professional development and life-long learning.
• Effective oral and written communication skills.
• Collaborative and collegial spirit and a demonstrated ability to establish rapport with learners, colleagues, sponsor-employers, and members of the community.
• Ability to initiate applied research projects.