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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- The Chinese University of Hong Kong
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, Machine Learning and Artificial Intelligence, Statistics, Management Science, and other closely related areas. Junior applicants must demonstrate a clear and high potential of teaching excellence. Senior
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/virtual/mixed reality (VR, AR, XR) Games and Interactive Media Computer graphics and 3D animation Computational design and generative fabrication Art/science research practices Requirement： All candidates
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and Sales Management, Business to Business or Industrial Marketing, Service Management and Marketing, Marketing Research, Marketing in China, Business Forecasting and Machine Learning, Deep Learning
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the establishment of four new Academies. The SE model aims to address future societal and industrial challenges through innovative education. To learn more, visit www.xjtlu.edu.cn . ABOUT THE ACADEMY
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intelligence, computer vision, mobile robotics, machine learning, data science and analytics, or be able to demonstrate an equivalent professional practice and engagement. Previous experience in coding (C/C
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innovative learning and teaching, and research, XJTLU draws on the strengths of its parent universities, and plays a pivotal role in facilitating access to China for UK and other institutional partners
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Professor, Research Interests: Computational and Applied Mathematics, Machine Learning and Data Science, Email: wukl@sustech.edu.cn 5. Ziming Ma, Associate Professor, Research Interests: Complex Geometry
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, Interdisciplinary Fields 3. Statistics: Machine Learning, Big Data Analysis III. Recruitment positions: Senior Positions (Top and Leading Talents), Junior Positions (Young Talents, Post Doctors) 1.Top Talents
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contributions in one or more of the following key areas: computational modeling of chemical systems, AI-driven materials discovery/design, robotics for chemical synthesis, machine learning applications in
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particle physics or related areas prior to the time of employment. Preferences will be given to those with experiences in collider phenomenology, machine learning, effective field theories, positivity bounds