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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability
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discipline. They should demonstrate good knowledge of quantitative and/or qualitative analysis; have a good command of written and spoken English and Chinese (advantage); have good interpersonal skills and a
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spoken Cantonese) and English quantitative research skills (including in survey development and multilevel data analysis) and/or qualitative research skills (including in developing interview schedule 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
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Science, Biomedical Sciences/Engineering, Electrical Engineering, Medical Physics, or related disciplines with a strong background in artificial intelligence and medical image analysis. Experience in deep learning
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experience in one or more of the following areas: development of methods for multi-omics data integration, application of machine learning models in life science, single cell data analysis and spatial
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. Previous work experience in big data analysis, managing large databases of research projects relating to family caregivers of older adults and/or cost effectiveness evaluation, and with related track records
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learning in imaging analysis, clinical trials, epidemiology, genetic study, big data analysis, R language or related statistic software, or/and Python software, or programming skills of deep learning tools
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or public sciences; (ii) proficiency in English; (iii) solid experience in ophthalmology and visual sciences research, deep learning in imaging analysis, clinical trials, epidemiology, genetic study, big data
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-seq and single-cell data analysis, and able to work independently and in a team. Preference will be given to those with work experience in immunology, AIDS and SARS-CoV-2. The appointee is expected