THE UNIVERSITY OF HONG KONG
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Work type: Full-time
Department: Department of Urban Planning and Design (01300)
Categories: Senior Research Staff & Post-doctoral Fellow
Post-doctoral Fellow (Urban Intelligence) in the Department of Urban Planning and Design (Ref.: 520201)
Applications are invited for appointment as Post-doctoral Fellow (Urban Intelligence) (2 posts) (Ref.: 520201), to commence as soon as possible, on a one- to two-year temporary basis, with a possibility for further extension depending on performance and funding availability. Applicants should have a strong commitment to data-driven research of the highest quality and long-term societal value. If appointed, candidates will focus on one or more of the following directions:
- To build data-driven decision support systems for urban decision-makers. Applicants with strong interest and understanding in one or multiple of the following: (i) spatial data mining and analytics, machine learning, (ii) spatial optimization, (iii) generative methods, and (iv) operations research and decision analysis, will be preferred.
- To build a knowledge database (graph) based on spatiotemporal causal analytics of carbon behaviors and urban systems. Applicants with a strong background in carbon science, machine learning and/or knowledge graph analytics will be preferred.
- To derive universal understandings of urban systems using spatiotemporal big data and statistical physics perspectives. Applicants with a good understanding of network analysis, statistical physics, mathematical modeling, and/or a strong curiosity about urban science will be preferred.
The appointees will join an interdisciplinary research group with expertise in urban science, spatial data science, machine learning, and math, and work on high-impact projects with a potential for publication in inter-disciplinary journals. Exceptional candidates can further apply for HKU Research Assistant Professor positions after the successful completion of the Post-doctoral Fellowship when opportunity arises. Applicants should possess a Ph.D. degree and demonstrate a deep understanding of one or multiple of the required fields. They should also demonstrate (i) proficiency in computer programming, machine learning fundamentals, applied statistics, or the ability to learn fast; (ii) academic integrity; and (iii) a track record of high-quality publications.
Applicants should apply online and upload an up-to-date CV, a one-page research statement, and the contact information of two referees. Review of applications will start as soon as possible and continue until July 31, 2023, or until the posts are filled, whichever is earlier.
For inquiries or ideas beyond the scope, please contact [email protected].
The University is an equal opportunities employer and
is committed to equality, ethics, inclusivity, diversity and transparency
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