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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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with expertise and experience in (1) Generative Modeling, (2) Multimodal Learning, (3) Generative AI and Computer Music, and (4) Efficient AI. Duties The appointees will be required to: (a) conduct
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) have strong knowledge of and background in electromagnetic device design, power electronics and machine learning; (c) have hands-on experience in electrical and electronic engineering; (d) have
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challenge issues, using advanced machine learning models and necessary techniques; (d) evaluate and validate the performance of proposed methods and algorithms through theoretical analysis; (e) maintain
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-inspired learning algorithms for efficient, robust and scalable pattern recognition; (b) assist in general management of the project; and (c) perform any other duties as assigned by the project leader
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willing to work in a collaborative environment. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high