Tenure-track professor/associate professor/assistant professor in hku business school and the school of computing and data science

Applications are invited for a joint appointment as Professor/Associate Professor/Assistant Professor in Statistics in HKU Business School and the School of Computing and Data Science, to commence as soon as possible. Appointment will be made on a three-year fixed-term basis, with the possibility of renewal and consideration for tenure before the expiry of a second three-year contract. Exceptionally outstanding candidates at Professor/Associate Professor level may be considered for appointment on tenure terms., The appointee is expected to:

• develop and maintain a vigorous, high-quality research agenda with a strong AI and data science component;
• publish in leading peer-reviewed journals and present at major international conferences;
• seek and secure external competitive research funding;
• contribute to teaching at undergraduate and postgraduate levels in statistics, data analytics and related areas, including AI-rich programme offerings;
• supervise research postgraduate students; and
• undertake service and administrative duties in HKU Business School, the School of Computing and Data Science, and the University as appropriate. Those appointed at Professor/Associate Professor level will also be expected to mentor and nurture the next generation of scholars and researchers, and assume high-level service/administrative responsibilities.

Applicants should possess a Ph.D. in Statistics, Data Science, Computer Science, Econometrics or a closely related field. The ideal candidate will:

• demonstrate a robust research record in statistics and/or machine learning, with applications in business, economics, finance, insurance or related areas;
• show evidence of, or potential for, cross-disciplinary research that bridges statistics, AI and business;
• exhibit a strong commitment to excellence in both research and teaching; and
• for appointment at Professor/Associate Professor level, have an international reputation and proven academic leadership in their field.

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary. Housing benefits will be provided as applicable.

HKU Business School

The School of Computing and Data Science

We are seeking outstanding scholars whose research and teaching lie at the interface of modern statistical methodology, artificial intelligence and data science, and who can contribute to cross-disciplinary collaborations between HKU Business School and the School of Computing and Data Science. The appointee will have their tenure home in HKU Business School (Statistics Group), and will be jointly appointed to the School of Computing and Data Science. As an AI+Business hire, the appointee is expected to develop a creative and impactful programme of research and teaching that integrates advanced statistical methods and AI with business, economics, and insurance and to play a leading role in fostering collaborations across the two units.

The Statistics Group in the Innovation and Information Management (IIM) Area at HKU Business School

The Statistics Group in the IIM Area at HKU Business School focuses on statistics and business analytics. The Group’s main research interests span the frontiers of modern statistical methodology and applications, including (but not limited to) machine learning, artificial intelligence, high-dimensional statistical inference, functional data analysis, time series analysis, econometrics, factor models, and privacy protection. The Group’s research is widely applied in areas such as healthcare and bioinformatics, service engineering, financial markets, educational assessments, and psychological measurement. The appointee is expected to complement and strengthen these areas, and to contribute to the Group’s growing portfolio of AI- and data-driven business analytics research.