Research Assistant Professor, Division of Industrial Data Science
- Employer
- LINGNAN UNIVERSITY
- Location
- Tuen Mun, Hong Kong
- Closing date
- 11 Dec 2024
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- Academic Discipline
- Computer Science, Engineering & Technology
- Job Type
- Academic Posts, Lecturers / Assistant Professors
- Contract Type
- Fixed Term
- Hours
- Full Time
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:
Research Assistant Professor
Division of Industrial Data Science
(Post Ref.: 24/336)
The Division is looking for experienced Research Assistant Professors who will (i) carry out research and submit papers to top journals in the field of large vision models, computer vision, and so on. Additionally, the appointees will be responsible for submitting grant proposals to various funding bodies. Furthermore, the appointees will have the opportunity to organize conferences, seminars, reading groups, workshops, and other related research activities; (ii) play a central role in the daily operation of the upcoming new Taught Postgraduate programme(s) offered by the Division of Industrial Data Science. The teaching load will be two courses per year, distributed according to the needs of the Institute and upon mutual agreement. English will be the medium of instruction. The appointees will also be required to supervise students’ projects or thesis; and (iii) perform administrative duties as assigned by the Associate Dean (i.e., Person-in-charge of Division of Industrial Data Science).
General Requirements
Candidates should have (i) a PhD degree in Data Science, Artificial Intelligence, Computer Science, Computer Engineering, or a relevant discipline; (ii) a good command of both English and Chinese; (iii) a strong publication record in the top-tier journals/conferences in the relevant field; and (iv) experience in developing external competitive research proposals. Candidates with a good teaching record will be an advantage.
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. Appointments 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 posts are filled. Qualified candidates are advised to submit their applications early for consideration.
The University reserves the right not to make an appointment for the posts advertised, or to fill the posts by invitation or by search. We regret that only shortlisted candidates will be notified.
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