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Deadline 9 Apr 2026 - 00:00 (UTC) Country Hong Kong Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related
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Department of Land Surveying and Geo-Informatics Research Assistant Professor in Geospatial Artificial Intelligence (GeoAI) / Geomatics / Global Change Ecology / Urban Science and Sustainability
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Department of Computing Research Assistant Professor (six posts) (Ref. 251009002) The Department of Computing (COMP) of The Hong Kong Polytechnic University, founded in 1974, pioneers
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Imaging (MRI) system that enables researchers to explore the structure and function of human brain. A high-performing computing server has been set up to support MRI data analysis. Responsibilities: Manage
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experience in managing and analysing large and complex datasets; expertise in Computational Social Science and proficiency in longitudinal analyses, multilevel modelling, data visualisation, and state
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projects on-time with minimum supervision. Preference will be given to those with research experience in machines design and development of computer programmes for numerical computation of electromagnetic
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Department of Land Surveying and Geo-Informatics Research Assistant Professor in Space Science (Ref. 251211003) The Department of Land Surveying and Geo-Informatics (LSGI) is widely considered as a
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Vincent C. Müller (FAU Erlangen‑Nürnberg). On the research side, the appointee will pursue an independent research programme in the philosophy of AI and participate in the activities of the AI & Humanity
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Department of Industrial and Systems Engineering Postdoctoral Fellow (Full-time/Part-time) (Ref. 260401006) [Appointment period: eight months] Duties The appointee will assist the project leader in the research project - “Next generation of in-situ precision three-dimensional surface metrology:...
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large