Assistant/Associate Professor in Marketing Analytics & Artificial Intelligence – Canadian University Dubai

Job Description

Canadian University Dubai (CUD) invites applications for Assistant Professor and Associate Professor positions in Marketing Analytics & Artificial Intelligence within the School of Management.

The position is based in Dubai, United Arab Emirates, with an anticipated start in Spring Semester 2026–2027.

Job ID: 236
Employment Type: Full Time
Posting Date: September 21, 2026
Application Deadline: October 23, 2026 at 11:00 PM
Location: City Walk, Al Wasl Road, Dubai, UAE

About the Position

Canadian University Dubai is seeking faculty who can contribute to:

• High-quality undergraduate and graduate teaching.
• Impactful academic research.
• Curriculum development.
• Student supervision.
• Academic service.
• Industry engagement.
• The wider academic development of the School of Management.

The position has a strong interdisciplinary focus combining marketing, consumer analytics, artificial intelligence, machine learning, predictive modelling, and data-driven decision-making.

Qualifications

Applicants must hold a PhD in Marketing, Marketing Analytics, or a closely related discipline.

The doctoral degree must have been obtained from a university ranked within the top 500 of the QS World University Rankings.

Candidates should demonstrate:

• Strong teaching effectiveness.
• Research productivity appropriate to academic rank.
• Engagement with industry and/or professional communities.
• Publications in reputable, Scopus-indexed journals, commensurate with academic rank.

Relevant professional certifications are preferred.

Areas of Expertise

Candidates should demonstrate expertise in areas including:

• Marketing and consumer analytics
• Artificial intelligence applications in marketing
• Machine learning applications in marketing
• Predictive modelling
• Quantitative and experimental methods
• Statistical modelling
• Data visualization
• Analysis of structured and unstructured consumer and digital data

Proficiency in analytical and programming tools such as Python and/or R is highly desirable.

Experience with business intelligence and visualization platforms such as Power BI and/or Tableau is also highly desirable.

Additional relevant analytical techniques include:

• Text mining
• Image analytics
• Topic modelling
• Clustering
• Social-network analysis
• Machine learning
• Business intelligence
• Data visualization

These capabilities are particularly relevant to the analytical and technical content of the MScDMA curriculum.

Experience Requirements

Applicants should demonstrate university-level teaching experience appropriate to the academic rank for which they are applying.

Relevant experience should include contributions to areas such as:

• Curriculum development.
• Student supervision.
• Academic service.

Candidates applying at the Associate Professor level should additionally demonstrate appropriate experience in undergraduate and graduate teaching and postgraduate supervision, commensurate with the requirements of that rank.

Experience in the following areas would be advantageous:

• Curriculum development.
• Supervision of graduation projects.
• Supervision of postgraduate research.
• AACSB accreditation processes.

Teaching Areas

Teaching may include undergraduate and graduate courses in:

• Marketing analytics and predictive modelling
• Artificial intelligence and machine learning applications in marketing
• Marketing research and data-driven decision-making
• Consumer and customer analytics
• Quantitative and experimental methods
• Social media analytics
• Digital consumer behaviour
• Data visualization and business intelligence
• Analysis of structured and unstructured consumer data
• Ethics and responsible artificial intelligence in marketing

Research Expectations

Successful candidates will be expected to maintain an active research agenda and publish in reputable, peer-reviewed journals.

Research areas may include:

• Marketing and consumer analytics.
• Predictive modelling.
• Artificial intelligence and machine learning applications in marketing.
• Digital consumer behaviour.
• Social media analytics.
• Structured and unstructured consumer data analysis.
• Responsible use of artificial intelligence and data in marketing.

Faculty members are also expected to engage with industry and professional communities to strengthen applied research, knowledge exchange, and professional practice.

Key Responsibilities

The successful candidate will be expected to:

• Serve as a subject matter expert and support the Program Chair or Coordinator in academic operations.
• Help maintain curriculum alignment with CUD requirements, industry needs, and developments in the discipline.
• Teach undergraduate and graduate courses in relevant areas of expertise.
• Maintain current course content and updated syllabi.
• Complete assessment and grading in a timely manner.
• Maintain accurate student records.
• Hold regular office hours and provide academic support and advising.
• Recommend suitable learning resources, technologies, and teaching materials.
• Supervise independent studies, student projects, internships, graduation projects, and postgraduate research as appropriate to academic rank.
• Contribute to curriculum evaluation and course development.
• Conduct high-quality research and publish in reputable peer-reviewed journals.
• Participate in academic governance, faculty meetings, accreditation processes, and academic documentation.
• Contribute to AACSB-related activities where applicable.
• Support student advising, registration, and orientation activities.
• Participate in community outreach, industry collaboration, and knowledge exchange.
• Represent CUD at conferences, professional events, and relevant public engagements.
• Participate in professional development and capacity-building activities.

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Compensation and Benefits

Eligible faculty employees may receive:

• Generous academic annual leave.
• Tax-free salary.
• Housing allowance.
• Transportation allowance.
• Annual flight benefits in accordance with faculty grade eligibility.
• Children’s education allowance in accordance with faculty grade eligibility.
• Furniture allowance where applicable.
• Joining and repatriation benefits in accordance with faculty grade eligibility.
• Family visa support in accordance with faculty grade eligibility.
• Professional development opportunities.
• International health insurance.
• Life insurance.
• In-house visa and relocation support.
• Full access to campus facilities.
• Research and innovation funding support.

Application Deadline

Applications should be submitted by:

October 23, 2026 at 11:00 PM

Applicants should verify all vacancy information and application requirements through the official Canadian University Dubai recruitment system before applying.