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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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- UNIVERSITY OF MACAU
- ; Xi'an Jiaotong - Liverpool University
- Sun Yat-sen University
- UNIVERSITY OF NOTTINGHAM NINGBO CHINA
- Xi'an Jiaotong-Liverpool University
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students the skills and knowledge they need to secure careers in a global marketplace. XJTLU now has over 25,000 enrolled students in both Suzhou and Liverpool in the UK, with plans to grow to about 28,000
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for teaching courses that integrate these areas, ensuring students develop both theoretical knowledge and practical competencies to excel in this rapidly evolving field. Beyond teaching, successful candidates
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international education experience, XJTLU brings together excellent research practice and expertise from both institutions and gives students the skills and knowledge they need to secure careers in a global
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excellent research practice and expertise from both institutions and gives students the skills and knowledge they need to secure careers in a global marketplace. XJTLU now has over 25,000 enrolled students in
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in studying and/or working at first-rate teaching and research institutions, and knowledge of the latest international trends and development in the relevant research fields. The applicant for Tenure
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. Offering a unique international education experience, XJTLU brings together excellent research practice and expertise from both institutions and gives students the skills and knowledge they need to secure
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, Computational Biology, Computer Science, or a related quantitative discipline. Strong statistical, computational, and communication skills are highly desired. A keen interest in gaining knowledge in medical and
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brings together excellent research practice and expertise from both institutions and gives students the skills and knowledge they need to secure careers in a global marketplace. XJTLU now has around 25,000
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gives students the skills and knowledge they need to secure careers in a global marketplace. XJTLU now has around 25,000 enrolled students in both Suzhou and Liverpool in the UK, with plans to grow
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working on statistics learning, granular computing and knowledge discovery, machine learning, deep learning, and specifically interpretable artificial intelligence. Many innovative contributions have been