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) Country Hong Kong Application Deadline 16 Sep 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
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, Computer Science, or related disciplines. They should have an excellent command of written and spoken English and Chinese; outstanding communication skills; and the ability to multitask and work independently as
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well-trained and enthusiastic mechanical and building service engineers and research graduates and to serve the local and international community and industry. Applicants should possess a PhD degree in
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to three years on fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability. Applicants should hold a PhD degree in epidemiology, biostatistics, public
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for RAP, or a one- to three-year temporary basis for PDF, with the possibility of renewal subject to satisfactory performance and funding availability. Applicants should possess a PhD in epidemiology
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of medicines. We welcome imaginative and interdisciplinary applicants who can move our ambitions forward by pursuing new opportunities for laboratory and clinical research programme. Applicants should possess a
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the following: PhD and/or MD degree in Biomedical Engineering, or in STEM-related fields. Distinguished record of academic achievements and international recognition in research, scholarship and teaching. Proven
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, Statistics, Computer Science, or a related discipline. Priority will be given to those with an outstanding research track record and extensive expertise in cancer bioinformatics, cancer biology, cancer
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. The appointees will teach courses of the Master of Arts in Creative Communications (MACC) Programme related to Social Media, Branding, and Marketing or other relevant fields of specialization. The MACC is a full
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students each year. In addition to these, the Faculty also hosts the Law, Innovation, Technology and Entrepreneurship (LITE) Programme (LITE, established in 2018), as part of the Experiential Learning