63 software-formal-method-phd positions at Hong Kong Polytechnic University in Hong Kong
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) experience in quantitative or mixed-methods data analyses; (c) experience in academic publications; (d) strong communication skills in English and Chinese; and (e) good interpersonal skills and the
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- “Development of high-performance two-dimensional material based ultrafast photonic and optoelectronic devices using aerosol jet printing method”. Qualifications Applicants for the Research Fellow post should
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. Applicants should also: (a) have a good command of both written and spoken English and Chinese, with fluency in Cantonese; (b) be proficient in using statistical software such as SPSS; and (c) be self
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to communicate with the U3DP for collaboration; and (c) sound knowledge of and solid experience in 3D printing technology, including the related software and drawing tools, printing materials and various
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facilities, including software and hardware, networks and servers, to ensure the smooth operation of the School’s teaching and research facilities; (d) provide technical assistance and support for online
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- “Research on methods for distributed workshop scheduling considering loading efficiency”. Qualifications Applicants should: (a) have an honours degree or an equivalent qualification; (b) have experience
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experience in branding, identity, graphic, publication/editorial design, as well as project administration and management; (b) have knowledge of using communication or graphic design related software in
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the research project - “White adipose tissue (fat) dysfunction in ageing and its related metabolic diseases: new insight and therapeutic intervention”. Qualifications Applicants should have: (a) a PhD degree
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machine learning methods, particularly large language models (LLMs), to marketing research. Applicants are invited to contact Prof. Edward Lai at telephone number 2766 7141 or via email at edward-yh.lai
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responsibility. Preference will be given to those with interest and potential in pursuing a PhD in Innovation Management. Applicants are invited to contact Prof. Ryan Wang at telephone number 2766 7357 or via