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of Physics (Ref.: 534748). Applicants should possess a Ph.D. degree in Condensed Matter Physics. Experience in numerical techniques and analytical field-theoretical approaches is desirable. Applicants who
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Computational and Theoretical Condensed Matter Physics in the Department of Physics (Ref.: 534748). Applicants should possess a Ph.D. degree in Condensed Matter Physics. Experience in numerical techniques 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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perform numerical simulations. Key Requirements for Postdoc: Requires a PhD in Physics or closely related disciplines. Experience with numerical software (VASP, Quantum Espresso) and programming (e.g
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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