Job Overview
More Information
- Address The Hong Kong University of Science and Technology (Guangzhou), Guangdong Province, China
- Qualification PhD
- Apply Before Open Until Filled
- Discipline Science & Engineering
- Last Refreshed Feb 14, 2022
- Department/School Website infh.hkust-gz.edu.cn/en
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Job ID:5639
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Department: Data Science and Analytics Thrust
Job Posting Details
Introduction of HKUST(GZ):
In the rapidly changing environment of the 21st century, there is an increasing need to forge bridges across disciplines to address emerging challenges and problems. Through its commitment to academic excellence, The Hong Kong University of Science and Technology (HKUST) has developed world-class strengths in many subjects over its short 30-year history. With a strong track record of cultivating high end talents and nurturing future leaders for academia and industry, HKUST is well positioned to craft an innovative approach to cross-disciplinary education and research in its Guangzhou campus, HKUST(GZ), and meet the needs of an ever-evolving world.
Introduction of Information Hub:
The Information Hub focuses on addressing global challenges arising from human interactions with information and technology in today’s era of digital transformation. We are committed to provide world-class education and conduct cutting-edge research with practical applications in information science and technology that not only advance regional development, but also make a global impact. The Hub primarily comprises four thrust areas: Artificial Intelligence (AI), Data Science and Analytics (DSA), Internet of Things (IOT), and Computational Media and Arts (CMA). We will achieve this mission through cross-disciplinary research and education in collaboration with other thrust areas in our Guangzhou campus and related programs in our Clearwater Bay campus. We welcome students from diverse backgrounds, ranging from Computer Science, Statistics, and Engineering to Business, Design, and the Arts.
Qualification of Candidates
Applicants with a Ph.D. degree who have worked on the following research topics or in a related field are encouraged to apply:
- Statistics;
- Deep learning theory;
- statistical machine learning.
The appointees are expected to play a key role in advancing the frontier of theoretical and/or practical research and demonstrate strong potential for securing research grants.
Preferred qualifications:
Strong mathematical foundations on
- Nonparametric/high-dimensional statistics;
- Machine learning/deep learning theory;
- Stochastic processes.
Strong practical computer science background in
- Strong programming skills.
Remuneration and Conditions of Service
Salary is highly competitive of international standard and will be commensurate with qualifications and experience. Generous research funds, ample laboratory space and excellent research equipment and support will be provided.
All posts are Mainland China appointment to be offered by the HKUST Mainland entity in accordance with the local employment laws and regulations. Initial appointments will be made on a fixed-term contract of 1 – 2 years commencing immediately. Re-appointment thereafter will be subject to performance, mutual agreement and funding availability.
Application Procedure
Please submit the application via the HKUST/HKUST(GZ) Recruitment System (https://facrecruit.hkust.edu.hk/). You should first sign up to create your personal account. Please select “Research Track” in “Non-tenure Stream”. For more information, please visit the recruitment website (https://gz-faculty-recruitment.hkust.edu.hk/).
Review of applications will continue until all positions are filled. We thank applicants for their interest. Please be advised that only shortlisted candidates will be notified of the result of their application.
For questions regarding the recruitment system or general inquiries, please reach us at facultyhire@ust.hk. For Hub/Thrust specific questions, please address to gzrecruitinf@ust.hk with subject title of “Application to PDF-DSA”.
(Information provided by applicants will be used for recruitment and other employment-related purposes. All application materials including publication samples and scholarly/creative works will be disposed of after the completion of the recruitment exercise.)
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