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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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) at Xi'an Jiaotong-Liverpool University is growing in size and influence in pursuit of its vision to be a leading international business school. The school is based on strong principles of internationalism
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-Liverpool University is growing in size and influence in pursuit of its vision to be a leading international business school. The school is based on strong principles of internationalism, innovation
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(R1) Country China Application Deadline 22 Oct 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
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team of about 30 faculty members, all of whom are actively engaged in cutting-edge research, teaching, and industry collaboration. As a key embodiment of XJTLU’s 3.0 vision, CIE is committed to serving
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in pursuit of its vision to be a leading international business school. The school is based on strong principles of internationalism, innovation, inspiration and integrity, which together ensure
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existing research areas. The department is involved in the delivery of undergraduate physics and mathematics modules at all levels, as well as the PhD programme. ROLE OVERVIEW Reporting to the Dean
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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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at XJTLU is one of the major schools in the University where we have about 2500 mathematics related majors. We have a Ph.D., Program where our graduates receive a PHD from the University of Liverpool
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: (1) advising on education strategy and vision, and leading university-wide developments in learning, teaching, and education innovation, and (2) ensuring operational excellence, agility and flexibility
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internationally. Responsibilities and Duties We are looking for future colleagues in all fields of computer science, data science, artificial intelligence, machine learning, deep learning, computer vision, natural