Assistant Professor of Teaching, Division of Industrial Data Science
- Employer
- Lingnan University
- Location
- Tuen Mun, Hong Kong
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- Faculty Jobs
- Engineering & Mathematics, Science & Technology, Computer Science & Information Technology
- Position Type
- Assistant Professor
- Employment Type
- Full Time
- Institution Type
- Four-Year Institution
Lingnan University is one of the eight publicly funded institutions in the Hong Kong Special Administrative Region (HKSAR) and has the longest established tradition among the local institutions of higher education. It is widely recognised for providing quality education with a focus on whole-person development and conducting high-impact research for a better world. Moving forward, Lingnan University aspires to become a comprehensive university in arts and sciences in the digital era, with impactful research and innovations.
Lingnan University offers undergraduate, taught postgraduate, and research postgraduate programmes in the Faculties of Arts, Business, Social Sciences, and the Schools of Data Science, Graduate Studies and Interdisciplinary Studies. To foster interdisciplinary collaboration and scientific progress, Lingnan University established the Lingnan University Institute for Advanced Study (LUIAS), attracting distinguished scholars from around the world to collaborate with its faculty and students. With traditional strengths in arts, business, social sciences, and interdisciplinary studies, the University aims to equip students with practical knowledge and critical thinking skills to thrive in the future. Subsequent to the establishment of the School of Data Science and LUIAS, Lingnan University is transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/.
Applications are now invited for the following posts:
Assistant Professor of Teaching
Division of Industrial Data Science
(Post Ref.: 24/338)
The Division is looking for experienced Assistant Professor of Teaching who will (1) teach multiple subjects in both undergraduate-level and postgraduate-level programmes in data science areas focusing on industrial data sciences, blockchain, data sciences, artificial intelligence, etc., (2) work on the promotions and admissions as well as the operations for undergraduate and postgraduate programmes, and (3) contribute to other administrative duties as required by the supervisors.
General Requirements
Candidates should have (i) a doctoral degree in a relevant data science, computer science, business, information systems, artificial intelligence, or other relevant areas; (ii) at least 3 years experience in teaching relevant courses and relevant programme administrative experience are required; and less teaching experience is also considered when the candidate has strong project or industrial experience, and (iii) good command of English and Chinese (including Mandarin).
Appointment
The conditions of appointment will be competitive. The remuneration will be commensurate with qualifications and experience. Fringe benefits include annual leave, medical and dental benefits, mandatory provident fund, gratuity and incoming passage and baggage allowance for the eligible appointee. Appointment will normally be made on a fixed-term contract of up to three years.
Application Procedure (online application only)
Please click "Apply Now" to submit your application. Applicants shall provide names and contact information of at least three referees to whom applicants consent has been given for their providing references. Personal data collected will be used for recruitment purposes only.
We are an equal opportunities employer. Review of applications will continue until the post is filled. Qualified candidates are advised to submit their applications early for consideration.
The University reserves the right not to make an appointment for the post advertised, or to fill the post by invitation or by search. We regret that only shortlisted candidates will be notified.
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