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: The successful candidate will be expected to: Carry out high-quality research under the supervision of our experienced faculty members. Participate in the development of theories, and perform numerical simulations
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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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subject to satisfactory performance and availability of funding. Duties and Responsibilities To conduct research on the numerical modeling of giant-planet magnetospheres, with a primary emphasis on
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To conduct research on the numerical modeling of giant-planet magnetospheres, with a primary emphasis on Jupiter’s magnetosphere–ionosphere system. The successful candidate will lead and analyze global
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. The Center emphasizes rigorous measurement, causal analysis, and clear communication of research findings. The Center is a joint initiative of the Faculty of Social Sciences and the Economics Department at HKU
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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
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
considered for appointment as a Senior Research Assistant. The appointee will work closely with the Principal Investigator and the project team in the “Psychometric and Statistical Analysis for Assessing
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, analysis and deep learning, 2) biostatistics and health/clinical data analysis or 3) cellular and molecular techniques will be an advantage. Opportunities for publication and independent development will be
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning