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Associate Professor/Assistant Professor in Operations and Business Statistics in the Department of Management Sciences [Ref. B/329/09]

City University of Hong Kong is a dynamic, fast-growing university that is pursuing excellence in research and professional education.  As a publicly-funded institution, the University is committed to nurturing and developing students’ talents and creating applicable knowledge to support social and economic advancement.  The University has nine Colleges/Schools.  As part of its pursuit of excellence, the University aims to recruit outstanding scholars from all over the world in various disciplines, including business, creative media, data science, energy and environment, engineering, humanities and social sciences, law, science, veterinary medicine and life sciences. 

Being an international university in a global city of Hong Kong, City University has been ranked amongst the top 25 schools in QS Asia University Rankings (2019).  The Department of Management Sciences within the College of Business has attained international recognition, with a strong group of researchers specializing in operations management and business analytics.  The Department now invites applications for multiple tenure-track faculty positions in the following areas.

The Department seeks strong candidates in analytics and business statistics.  Specialization is open, but preference will be given to those with expertise in big data analytics, business and financial statistics, data-mining, statistics in healthcare management, and survey sampling.  Candidates for Associate Professor should possess a PhD, a substantial publication record in high quality statistics journals or other high quality journals that are known for publishing statistics-discipline related papers, and dedication to quality teaching with relevant experience. They are expected to provide contribution/leadership in research, plan curriculum of studies and supervise PhD students.  Candidates for Assistant Professor should possess a PhD, completed or near completion, and good potential for publishing in high quality journals.  Preference will be given to those candidates with research and teaching interests in applied statistics, business analytics, machine learning or a closely-related field.

Successful candidates are expected to develop a vigorous research programme and teach courses in business statistics, operations analytics and related courses, initially at the undergraduate level and then at the postgraduate level (including MBA).

Salary and Conditions of Service

Remuneration package will be driven by market competitiveness and individual performance. Excellent fringe benefits include gratuity, leave, medical and dental schemes, and relocation assistance (where applicable). Initial appointment will be made on a fixed-term contract.

Information and Application

Further information on the posts and the University is available at http://www.cityu.edu.hk, or from the Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong (Email : msapril@cityu.edu.hk).

To apply, please submit an online application at http://jobs.cityu.edu.hk, and include a current curriculum vitae.  Applications received by 30 November 2019 will receive full consideration.  Only shortlisted applicants will be contacted; and those shortlisted for the post of Assistant Professor will be requested to arrange for at least 3 reference reports sent directly by the referees to the Department, specifying the position applied for.  The University's privacy policy is available on the homepage.

City University of Hong Kong is an equal opportunity employer and we are committed to the principle of diversity.  Personal data provided by applicants will be used for recruitment and other employment-related purposes.

Worldwide recognition ranking 52nd, and 4th among top 50 universities under age 50 (QS survey 2020); 1st in Engineering/Technology/Computer Sciences in Hong Kong (ARWU survey 2016); and 2nd Business School in Asia-Pacific region (UT Dallas survey 2017).

 

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