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focus on applying these numerical approaches to quantum many-body systems, such as correlated 2D materials, quantum Moire systems, frustrated magnets, topological order, quantum phase transitions beyond
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magnets, topological order, quantum phase transitions beyond Landau-Ginzburg-Wilson paradigms, etc. The recent works of Prof. Meng and the group can be found at https://quantummc.xyz/publication. A highly
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Kong University of Science and Technology (HKUST). Prof Law's research group is interested in general topics in condensed matter physics with emphasis on topological materials, moiré materials and
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highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times
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pillars such as Big Data Analytics and Management, Machine Learning and Optimization, AI for Data Science, Deep Learning, Generative Learning, Biometrics Processing, Natural Language Processing, Computer
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., proficiency in Python, PyTorch, OpenCV) and experience in deep learning model optimization and familiarity with AI model deployment are required. Candidates with experience in quantitative CT algorithms
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troubleshooting. The appointees will collaborate with software teams, ecology specialists, and biomedical experts to optimize device performance, as well as support manufacturing and scalability initiatives
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possess extensive experience in developing deep learning algorithms Excellent programming skills (e.g., proficiency in Python, PyTorch, OpenCV) and experience in deep learning model optimization and
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to optimize device performance, as well as support manufacturing and scalability initiatives. Enquiries about the duties of the posts should be sent to Mr. Eric Yip at yiperic@hku.hk . Information about the