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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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Learning are highly expected Preferred research directons: Numerical Optmizaton and Scientfc Machine Learning. A PhD in Mathematcs or Applied Mathematcs. Two years of full tme postdoctoral experience with
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positions at all academic ranks. We seek applicants with outstanding methodological foundations in one or more of the following areas: Computer Science, Operations Research, Data Science, Machine Learning and
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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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science, artificial 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
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an attractive salary between 400,000-500000 RMB/year (~58,000 - 70,000 USD). The project focuses on analyzing machine learning techniques using random matrix tools, with an emphasis on Empirical Risk Minimization
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salary between 400,000-500000 RMB/year (~58,000 - 70,000 USD). The project focuses on analyzing machine learning techniques using random matrix tools, with an emphasis on Empirical Risk Minimization (ERM
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, Machine Learning, Thesis, etc. (taught in English). Qualifications: Applicants must possess a Master Degree in a field related to Artificial Intelligence or Drug Discovery. Closing Date for Application : 14
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primary medium of instruction at UM. The Department of Electrical and Computer Engineering (ECE) in the Faculty of Science and Technology invites applications for multiple positions (Full/Associate
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] Subject Areas: Statistics and Data Science(including Machine Learning, Actuarial Science, Mathematical Finance, Bioinformatics, Artificial Intelligence etc) Appl Deadline: none (posted 2024/12/03) Position
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, quantitative finance, risk quantification, financial risk management, machine learning/AI in finance or similar areas depending on the evolving needs of the department. The successful candidates are also