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estimation; generate tables and figures for reports and presentations; write scientific publications, grant proposals and reports; and assist in general administrative, operational and other duties as assigned
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statistical research, and will work with a large population-based cohort with over 46,000 participants in 20,000 households. They will conduct power/sample size estimation; generate tables and figures
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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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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
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proficient in data analysis using statistical or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic
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. Applicant(s) should possess a Ph.D. degree, or equivalent, in biological or computer sciences or a related discipline. Experience in any of the following fields, including 1) biological image acquisition
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or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic research papers. They should be organized, self
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engineering, computer engineering and applied physics, with a solid academic background in biomedical imaging and AI and an excellent research track record. Candidates should demonstrate a strong academic track
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proficient in data analysis using statistical or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic
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or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic research papers. They should be organized, self