167 data-"https:"-"https:"-"https:"-"SAPIENZA---UNIVERSITA'-DI-ROMA" positions at Hong Kong Polytechnic University in Hong Kong
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Department of Data Science and Artificial Intelligence Postdoctoral Fellow (Ref. 260102012) [Appointment period: four months] Duties The appointee will assist the project leader in the research
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algorithm market success: code, data, and (pre-trained) models”. Qualifications Applicants should have an honours degree or an equivalent qualification. Applicants are invited to contact Prof. Xin Li
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three or more years of relevant research experience. Preference will be given to those with hands-on experience in laboratory research and data analysis. Applicants are invited to contact Prof. Chien-Ling
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of the project; (e) assist with data entry, analysis and management of project data; (f) assist in preparing work roster for volunteers; (g) assist in preparing progress and final reports of the project
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) ensure data security, privacy compliance and adherence to institutional and regulatory standards (e.g., GDPR, local data protection regulations); (d) manage technical deployment processes
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degree; (b) have knowledge of qualitative data analysis; (c) have a good command of academic writing in both English and Chinese; and (d) demonstrate competency in project coordination. Applicants
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) have a good knowledge of computer vision and programming skills; and (c) be willing to learn research methods, data processing and data analysis. Applicants are invited to contact Prof. Lawrence W. C
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4067 or via email at x.li@polyu.edu.hk for further information. Conditions of Service A highly competitive remuneration package will be offered. The closing date for application is 31 January 2026
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. Applicants are invited to contact Prof. Qing Li at telephone number 2766 7252 or via email at qing-prof.li@polyu.edu.hk for further information. Conditions of Service A highly competitive remuneration
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”. They will be required to: (a) construct high-quality data pipelines covering code, mathematics and general-domain data, as well as ensure data clarity, diversity and scalability; (b) develop efficient