62 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions in Hong Kong
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environment and governance will be highly desirable. Experience in computational social science, causal inference, text mining, machine learning, analysis of unstructured and multimodal data, or advanced
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for analytical methods, protocols, and reports and provide training on processes and equipment. Supervise and co-supervise undergraduate and postgraduate students. Disseminate research findings through
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13 Nov 2025 Job Information Organisation/Company THE UNIVERSITY OF HONG KONG Research Field Biological sciences Computer science Mathematics Researcher Profile Recognised Researcher (R2) Established
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of renewal subject to satisfactory performance. Applicants should possess a Ph.D. degree in Computer Science, Mathematics, Statistics, computational biology, related disciplines or equivalent. They should be
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data or job advertisements, as well as expertise in web crawling, large language models, and text analysis techniques. An excellent understanding of causal inference methods is essential to develop
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Kong Application Deadline 31 Dec 2025 - 00:00 (UTC) 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
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Ref.: 533792 Work type: Full-time Department: School of Nursing
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social sciences research methods Applicants should contact and secure mentors, one from each of FOSS (HKU) and ISR (Michigan) to get their interest and support in mentoring before making application What
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Ref.: 533638 Work type: Full
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should: Possess a Ph.D. in Economics, Public Policy, or a closely related discipline, with solid training in economics and quantitative research methods. Demonstrate strong research capability and a track