Assistant Professor/Lecturer (Artificial Intelligence/Cyber Security)

Hong Kong (HK)
Friday, 30 October 2020
End of advertisement period
Sunday, 8 November 2020
Contract Type
Full Time

Established by the Hong Kong Government in 1989, The Open University of Hong Kong today is the largest self-financing university in Hong Kong and has developed into a dynamic, innovative, full-fledged university comprising 6 Schools.

The University has been offering full-time programmes since 2001 and joined the Joint University Programmes Admission System (JUPAS) since 2007.  Currently, the University offers about 200 programmes of studies with around 10,000 full-time undergraduates and 1,000 postgraduates, and more than 8,000 part-time students in its 5 Schools namely School of Arts and Social Sciences, Lee Shau Kee School of Business and Administration, School of Education and Languages, School of Nursing and Health Studies and School of Science and Technology.  In addition, there are more than 2,000 full-time and 2,000 part-time students studying in Li Ka Shing School of Professional and Continuing Education (LiPACE).

The University strives to provide high quality and flexible university education at various levels, and to excel as a provider of higher education. Our full-time programmes for qualified secondary school leavers are on par with other established universities across Hong Kong. We are committed to advancing learning, knowledge, and research that meet students’ learning aspirations and society’s talent needs, focusing on practical and professional programmes. As a multi-mode university, we use innovative teaching and the latest education technology to offer world class education, guided by our core values of fairness, integrity, perseverance, and innovation.

We are now inviting application(s) for the following post in the School of Science & Technology:

Assistant Professor/Lecturer (Artificial Intelligence/Cyber Security) (Ref.: 20003NY)

Major Duties and Responsibilities

The appointee shall mainly be responsible for the following:

  • Undertaking course planning, development, coordination and delivery (including classroom teaching) in related disciplines at both the undergraduate and postgraduate levels;
  • Providing assistance in the course planning, development, coordination and delivery (including classroom teaching) in related disciplines;
  • Undertaking/engaging in academic research;
  • Engaging in scholarly activities; and
  • Participating in School/University activities and administration.


Applicants are expected to possess the following qualifications, experience and attributes:

  • An earned doctorate in Computer Science, Electronic Engineering, or a related discipline;
  • Relevant teaching experience in the areas of Deep Learning, Data Mining and Cloud Computing; or in the areas of Network Security, Digital Forensics and Blockchain;
  • Strong communication skills and the ability to use English as the medium of instruction; and
  • A record of publication and research funding will be an advantage;

Candidates with less experience may be considered at the level of Lecturer.

Please indicate in your CV for the position(s) that you wish to be considered.

Compensation Package

Competitive compensation package including basic salary, end-of-contract gratuity and discretionary incentive (if any) will be offered to the right candidate.  Fringe benefits such as generous annual leave, staff learning and development sponsorship, medical & dental benefits and life insurance coverage will also be provided.

Application Procedures

Application should be made online through the University’s eRecruitment System.

Deadline: 8 November 2020

General information about the University is available on the University’s website  Personal data provided by job applicants will be handled strictly in accordance with the University’s Personal Data Privacy Policy.  The “Personal Data (Privacy) Notice for Job Applicant” is also available on the above website.  Applicants who are not contacted by the University within eight weeks from the closing date may assume that their applications are unsuccessful.

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