Qihao Weng
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Postdoctoral Fellowships in GeoAI, Urban Climate, and Environmental Science at The Hong Kong Polytechnic University The Hong Kong Polytechnic University in Hong Kong
Degree Level
Postdoc
Field of study
Computer Science
Funding
A highly competitive remuneration package is offered. The position is fully funded for a period of twelve to thirty-six months. Specific stipend amounts and benefits are not detailed, but the post is described as offering a highly competitive package.
Deadline
Jun 30, 2026
Country
Hong Kong
University
The Hong Kong Polytechnic University

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About this position
The Department of Land Surveying and Geo-Informatics at The Hong Kong Polytechnic University is offering multiple postdoctoral fellowships in cutting-edge research areas including GeoAI, urban climate, environmental science, and sustainable development. These positions are part of the Research Centre for Artificial Intelligence in Geomatics (RCAIG), a collaborative initiative spanning five academic departments and three faculties, leveraging the JC STEM Lab of Earth Observations. The research environment is highly interdisciplinary, fostering innovation and collaboration across geoinformatics, artificial intelligence, and environmental studies.
Key research projects include the response of vegetation phenology to land surface temperature in major metropolitan areas across the Asian Monsoon regions, optimal use of satellite thermal infrared image data for advancing land surface temperature analysis and mitigating urban heat stress, climate resilience to extreme heat along urban-rural gradients in Asia, land-based climate adaptation and mitigation solutions, and foundational models and methodologies for GeoAI in smart and resilient cities. There is also scope for proposing novel research ideas within these broad themes.
Successful candidates will work under the supervision of Professor Qihao Weng, contributing to innovative research in urban climate, ecosystems, environment, and GeoAI. The positions offer a dynamic and supportive research culture, with access to advanced facilities and collaboration opportunities within RCAIG and the wider university community.
Applicants must have a doctoral degree (or equivalent) in a relevant field such as Remote Sensing, GIScience, Computer Science, Artificial Intelligence, Statistics, Geography, Urban Planning, Architecture, Geoscience, Environmental Science, Landscape Ecology, Meteorology and Climatology, Natural Resources, Agricultural and Forest Engineering, or Economics, with no more than five years of post-qualification experience. Essential skills include algorithm development, strong English communication, and a record of first-authored publications. Preferred qualifications include expertise in quantitative methods, geospatial data analysis, AI, computer vision, scientific computing (Python, R), high-performance and cloud computing, and the ability to work both independently and collaboratively.
The positions are fully funded for twelve to thirty-six months, with a highly competitive remuneration package. The application deadline is 30 June 2026. For more information about the team and Professor Weng, visit the provided links. Interested applicants should apply online and may contact Professor Weng for further details.
Funding details
A highly competitive remuneration package is offered. The position is fully funded for a period of twelve to thirty-six months. Specific stipend amounts and benefits are not detailed, but the post is described as offering a highly competitive package.
What's required
Applicants must hold a doctoral degree or equivalent in Remote Sensing, GIScience, Computer Science, Artificial Intelligence, Statistics, Geography, Urban Planning, Architecture, Geoscience, Environmental Science, Landscape Ecology, Meteorology and Climatology, Natural Resources, Agricultural and Forest Engineering, Economics, or a related field, with no more than five years of post-qualification experience. Required skills include experience in algorithm development and refinement, strong command of written and spoken English, and at least two first-authored publications. Preference is given to candidates with a strong background in quantitative methods, statistics, computer science, geospatial data analysis and modeling, experience in AI and geospatial computer vision, advanced skills in Python and R, experience in high-performance and cloud computing, ability to work independently and collaboratively, and a strong publication record.
How to apply
Apply via the provided online application link. Interested applicants may contact Prof. Qihao Weng for further information. Ensure all required documents and qualifications are prepared before submitting your application.
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