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Digital Marketing Faculty

Canadian University of Dubai 🇦🇪 Dubai, United Arab Emirates Posted 7 days ago
Full-timeMarketing Sponsors visas
Canadian University Dubai, CUD is seeking exceptional faculty at the ranks of Assistant Professor and Associate Professor in Digital Marketing and Analytics 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 expertise across contemporary areas of digital marketing, analytics, and technology enabled marketing practice. Qualifications Applicants must hold a PhD in Digital Marketing or a closely related field, obtained from a university ranked within the top 500 in the QS World University Rankings, preferably from an accredited Western institution. Candidates should demonstrate a strong record of teaching effectiveness, research productivity, and industry engagement. Evidence of publications in highly ranked, Scopus indexed journals is required. Relevant professional certifications are preferred. Prior experience within a Canadian academic institution is preferred, as is teaching experience in the Middle East. Preference will be given to candidates with Canadian affiliation through Canadian qualifications, teaching experience at a Canadian university, or other established academic or professional links to Canada or North America. Experience Requirements Assistant Professor, minimum 2 years of undergraduate teaching experience at a top 500 QS ranked university, including experience in curriculum development and supervision of graduation projects. Associate Professor, minimum 5 years of undergraduate and graduate teaching experience at a top 500 QS ranked university, including experience supervising MSc or DBA students. Familiarity with AACSB accreditation is preferred. Teaching Areas Teaching will span key areas of Digital Marketing and Analytics, including: • Digital marketing strategy and planning • Marketing analytics and predictive modelling • Marketing research and data driven dec

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