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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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. Preference will be given to those with expertise in innovative methods of advanced statistics and/or learning analytics, such as multiple linear regression, mediation analysis, mixed-effect models, process
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methods of advanced statistics and/or learning analytics, such as multiple linear regression, mediation analysis, mixed-effect models, process mining, epistemic network analysis and cluster analysis
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and Prevention Group of HKU (stroke.hku.hk) to assist in neuroimaging data acquisition and analysis, write-up of the results, as well as training of students Apply image analysis skills on clinical and
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value and student learning experience is crucial. Preference will be given to those with experience in qualitative analysis and advanced statistics such as Structural Equation Modelling, Multilevel
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. Expertise and knowledge in AI deep learning model development on histology whole slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and
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biomedical engineering (BME), biomedical sciences, biotechnology or a related discipline. A strong track record of teaching should be demonstrated including one or more of the following elements related
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or a related discipline. A strong track record of teaching should be demonstrated including one or more of the following elements related to training in contemporary biomedical engineering: Foundational
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courses in business and finance journalism, including but not limited to financial reporting, corporate governance, entrepreneurship, economics and financial analysis for journalists, sustainability and
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. They should have solid knowledge of chemistry and biology, and an excellent command of spoken and written English and Chinese. Experience in bioinformatic data analysis including microbiome, virome and