Marketing Analytics & Artificial Intelligence Faculty

Canadian University Dubai (CUD) is seeking exceptional faculty at the ranks of Assistant Professor/ Associate Professor in Marketing Analytics & Artificial Intelligence to join the School of Management starting Spring Semester 2026–2027. Successful candidates will contribute to high-quality teaching, impactful research, curriculum development, and the School’s broader academic initiatives, with particular expertise in marketing and consumer analytics, artificial intelligence, machine learning, predictive modelling, and data-driven marketing. Qualifications: Applicants must hold a PhD in Marketing, Marketing Analytics or a closely related discipline, obtained from a university ranked within the top 500 in the QS World University Rankings. Candidates should demonstrate a strong record of teaching effectiveness, research productivity, and engagement with industry and/or professional communities. Evidence of publications in reputable, Scopus-indexed journals is expected, commensurate with academic rank. Relevant professional certifications are preferred. Expertise: Candidates should demonstrate expertise in areas including: Marketing and consumer analytics Artificial intelligence and 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, together with data visualization and business intelligence platforms such as Power BI and/or Tableau, is highly desirable. Experience with advanced analytical techniques such as text mining, image analytics, topic modelling, clustering, social-network analysis, machine learning, and business intelligence/data visualization is also highly desirable, given the analytical and technical content of the MScDMA curriculum. Experience Requirements: Candidates should demonstrate relevant university-level teaching experience appropriate to the academic rank applied for, together with evidence of contribution to curriculum development, student supervision, and 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 the academic rank. Experience with curriculum development, supervision of graduation projects and/or postgraduate research, and familiarity with AACSB accreditation processes would be advantageous. Teaching Areas: Teaching will span key areas of Digital Marketing and Analytics, including: 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 Focus: Successful candidates will be expected to maintain an active research agenda and publish in reputable, peer-reviewed journals, with research expectations commensurate with academic rank and CUD requirements. Relevant research areas may include marketing and consumer analytics, predictive modelling, artificial intelligence and machine learning applications in marketing, digital consumer behaviour, social media analytics, analysis of structured and unstructured consumer data, and the responsible use of artificial intelligence and data in marketing. Candidates are also expected to engage with industry and professional communities to strengthen applied research, knowledge exchange, and professional practice. Key Responsibilities: Serve as subject matter experts, supporting the Program Chair or Coordinator in academic operations and helping ensure curriculum alignment with CUD requirements, industry needs, and current developments in the discipline. Teach undergraduate and graduate courses within their respective areas of expertise, ensuring engaging delivery, current course content, updated syllabi, and timely assessment and grading. Maintain accurate student records, hold regular office hours, provide academic support, and advise students as required. Recommend appropriate learning resources, technologies, and materials to enhance the student learning experience. Supervise independent studies, student projects, internships, graduation projects, and postgraduate research, as appropriate to academic rank. Contribute to curriculum evaluation, course development, and the continuous improvement of academic programs. Conduct high-quality research, publish in reputable peer-reviewed journals, and maintain active professional and scholarly engagement. Participate in academic governance, faculty and departmental meetings, accreditat

PhD in Marketing, Marketing Analytics or a closely related discipline, obtained from a university ranked within the top 500 in the QS World University Rankings. Strong record of teaching effectiveness, research productivity, and engagement with industry and/or professional communities. Evidence of publications in reputable, Scopus-indexed journals. Relevant professional certifications are preferred. Teaching experience appropriate to the rank, with experience in curriculum development, student supervision, and academic service. For Associate Professor: undergraduate and graduate teaching and postgraduate supervision experience; familiarity with AACSB accreditation processes is advantageous.

Teach undergraduate and graduate courses in Digital Marketing and Analytics, 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; supervise independent studies, student projects, internships, graduation projects, and postgraduate research; contribute to curriculum evaluation and course development; conduct high-quality research and publish in peer-reviewed journals; engage with industry and professional communities; participate in academic governance and committee work; assist Program Chair/Coordinator with curriculum alignment and accreditation readiness.