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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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/EXPERIENCE: Numerical machine leaning/Scientific Machine Learning are highly expected Preferred research directions: Numerical Optimization and Scientific Machine Learning. A PhD in Mathematics or Applied
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design with advanced technologies. He/she will apply expertise in areas such as mechanics, CAD/ CAE modelling and simulation, actuators/electronics/sensors technology, control, machine learning/programming
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, actuators/electronics/sensors technology, machine learning/programming, and related fields to drive cutting-edge mechanical and mechatronics design innovation, taking a hands-on approach and designing
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Engineering, Computer Science, Artificial Intelligence, Computer Vision, Mobile Robotics, Machine Learning, Data Science and Analytics, Applied Mathematics. Location: Taicang, Greater Suzhou, China ABOUT XJTLU
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expertise in areas such as automatic control, mechanics, CAD/ CAE modelling and simulation, actuators/electronics/sensors technology, machine learning/programming, and related fields to drive cutting-edge
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simulation, actuators/electronics/sensors technology, control, machine learning/programming, and related fields to drive cutting-edge mechanical and mechatronics design innovation, taking a hands-on approach
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recruitment of Associate/Assistant Professor in Business Intelligence and Analytics (AI Application in Business), with a focus on applied artificial intelligence (AI) or machine learning (ML) in business, or
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that blend industrial design with advanced technologies. He/she will apply expertise in areas such as machine learning/programming, physical ergonomics/cognitive ergonomics, electronics/sensors technology, or
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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