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: CNY 800,000/year (pre-tax). Performance-based incentives and research productivity bonuses for high-impact research achievements are uncapped. National Talent Program Recipients will qualify
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Computing, Edge Computing, Social Network Programming and Analysis, Intelligent Transportation. RESPONSIBILITIES Applicants will have extensive teaching experience, have published high quality papers in
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qualifications can also apply for special talent recruiting programs established by the national government, Peking University, or BICMR, such as Yangtze River Distinguished Professorship, Chair Professorship
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. National Talent Program Recipients will qualify for elevated compensation packages. Fast-tracked doctoral advisor eligibility forr Associate/Full(or part-time) Professors meeting the university's "Essential
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the next generation of engineers. Key Responsibilities Plan and lead the development and implementation of a research strategy in Electrical and Electronic Engineering, building national and international
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Computing, Edge Computing, Social Network Programming and Analysis, Intelligent Transportation. RESPONSIBILITIES Applicants will have extensive teaching experience, have published high quality papers in
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of undergraduate physics and mathematics modules at all levels, as well as the PhD programme. ROLE OVERVIEW Reporting to the Dean of the School of Mathematics and Physics, the Head of the Department (HoD) of Physics
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to apply for national, province and city level programs. These programs aim to support excellent scientists, both Chinese and non-Chinese-citizen, to work and carry out research in China. Some of the
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educational programs in creative technology. Lead the academy in the creation and production of digital content. Collaborate with XJTLU campus communities and partners to enhance the academy's ecosystem. Drive
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collaboration with industry partners, CIE co-designs solutions and talent development programs that address real-world challenges. The college emphasizes cross-disciplinary innovation, practice-oriented learning