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Canadian University Dubai (CUD) invites applications for faculty at the ranks of Assistant Professor and Associate Professor in Marketing Analytics and Artificial Intelligence to join the School of Management.
Successful candidates will contribute to teaching, research, curriculum development, and engagement with industry, with expertise in marketing analytics, AI, machine learning, and data-driven marketing.
Canadian University Dubai CUD is seeking exceptional faculty at the ranks of Assistant Professor Associate Professor in Marketing Analytics amp Artificial Intelligence to join the School of Management starting Spring Semester 2PHONE NUMBER 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
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
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
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 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
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
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 accreditation processes and related academic documentation Contribute to the School of Management s accreditation activities including AACSB-related initiatives where applicable Support academic administrative activities including student advising registration and orientation activities as required Engage in community outreach industry collaborations knowledge exchange and professional service Represent CUD at professional events conferences and relevant public engagements Participate in professional development and other capacity-building initiatives Our eligible faculty employees enjoy competitive compensation and benefits including Generous academic annual leave 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.