Full-Time Faculty, MSc. Artificial Intelligence (AI) Program at International Business University | CA | Rezi

Full-Time Faculty, MSc. Artificial Intelligence (AI) Program at International Business University

Full-Time Faculty, MSc. Artificial Intelligence (AI) Program

International Business University · CA

1 months ago

Full-Time Faculty, MSc. Artificial Intelligence (AI) Program

International Business University · CA

a month ago
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About the Role

As a Full-Time Faculty member in the Master of Science in Artificial Intelligence (AI) program, you will play a key role in the growth and success of one of IBU's newest graduate programs. Reporting to the Executive Dean and Vice-President, you will deliver high-quality teaching, develop curriculum, mentor students, and contribute to program enhancement, academic quality, and industry engagement. This role is ideal for a passionate educator and scholar committed to student success, innovation, and academic excellence.

Responsibilities

  • Develop, review, and deliver high-quality curriculum and course content within the Master of Science in Artificial Intelligence program.
  • Teach graduate-level courses using engaging, innovative, and evidence-based pedagogical approaches.
  • Support student learning and success through mentorship, academic advising, and timely feedback.
  • Contribute to the continued growth, enhancement, and accreditation readiness of the MScAI program.
  • Evaluate student performance and maintain accurate academic records in accordance with university policies and standards.
  • Analyze curricular trends, learning outcomes, and student success data to support continuous improvement initiatives.
  • Engage in scholarly, applied, and/or industry-based research activities that contribute to the advancement of the field.
  • Collaborate with faculty, academic leadership, and external stakeholders to strengthen program quality and industry relevance.
  • Participate in university service activities, committees, academic planning initiatives, and faculty meetings.
  • Contribute to a respectful, inclusive, and collaborative academic environment that supports student, faculty, and institutional success.

Requirements

  • Preference will be given to candidates with a terminal degree requirement and a demonstrated commitment to teaching and research.
  • PhD in Artificial Intelligence, Computer Science, Data Science, Machine Learning, or a closely related field is required.
  • Preference will be given to candidates who qualify as Scholarly Academic (SA) faculty under AACSB standards through a strong record of peer-reviewed intellectual contributions and demonstrated ongoing research productivity.
  • Demonstrated record of peer-reviewed scholarly publications and an active research agenda in Artificial Intelligence, Data Science, Machine Learning, Data Engineering, Industrial Innovation, or related fields.
  • Demonstrated record of having supervised graduate students.
  • Demonstrated record of industry engagement in AI driven innovation.
  • Expertise in areas such as machine learning, deep learning, data engineering, intelligent systems, robotics, or applied AI solutions.
  • Experience teaching topics including Artificial Intelligence, Machine Learning, Data Science, Data Engineering, Cybersecurity, Human-Computer Interaction, or AI applications in industry.
  • Demonstrated relevant academic background, research portfolio and a record of teaching excellence.
  • Experience with remote/online/hybrid instruction is desirable.
  • Application Packages should contain the following: A cover letter, A current CV, A statement of teaching philosophy and evidence of teaching effectiveness (e.g., examples of peer and/or student evaluations), A research plan (up to two single-spaced pages), Sample publications or a research portfolio, Indigenization, Equity, Diversity and Inclusion (I-EDI) Statement.
  • Contact information of three referees will be requested of longlisted candidates.

Skills

  • Artificial Intelligence
  • Computer Science
  • Data Science
  • Machine Learning
  • Deep Learning
  • Data Engineering
  • Intelligent Systems
  • Robotics
  • Applied AI Solutions
  • Cybersecurity
  • Human-Computer Interaction
  • AI applications in industry

Location

  • Toronto, Ontario

Work Type

  • Full-Time
  • Permanent
  • Hybrid

Experience Level

  • Graduate-level teaching experience
  • Supervised graduate students
  • Industry engagement in AI driven innovation

Education Level

  • PhD in Artificial Intelligence, Computer Science, Data Science, Machine Learning, or a closely related field

Salary/Compensations

  • $110,000 - $120,000 annually

Benefits

  • 100% employer-paid extended Health & Dental benefits
  • 24/7 access to an Employee and Family Assistance Program (EFAP) and virtual healthcare services
  • Life, Accidental Death & Dismemberment (AD&D), and Long-Term Disability insurance
  • Competitive paid time off, starting at three weeks
  • Tuition Benefit Program
  • Access to preferred corporate membership rates with GoodLife Fitness
  • Engaging employee appreciation and community-building events

About the Company

  • IBU is one of Canada's fastest-growing universities, committed to innovation, academic excellence, and preparing graduates to thrive in a rapidly changing global economy.
  • As a member of our faculty, you will have the opportunity to help shape and expand a growing graduate program, collaborate with talented colleagues and industry partners, and make a meaningful impact on the next generation of AI professionals, researchers, and leaders.

Equal Opportunity

  • IBU is an Equal Opportunity Employer.
  • IBU is committed to fostering a diverse, inclusive, and equitable workplace where everyone feels welcome, valued, and respected.
  • We are dedicated to the principles of equal opportunity and encourage applications regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.
  • Please contact careers@ibu.ca if you require accommodation during the recruitment process.