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quantitative research methods. Demonstrate strong research capability and a track record of publications in relevant fields. Have proficiency in data processing and statistical analysis, with experience in
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Policy, Social Work, or related disciplines. They should have strong knowledge and skills in statistical methods and quantitative research, as well as excellent academic writing skills. Candidates must
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the field of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R
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of research include quantum Monte Carlo methods, density matrix renormalization group and tensor network states, and artificial intelligence and neural networks, with particular focus on applying
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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independently and as a team. Knowledge and experience in using mixed research methods are highly preferred. A strong publication track record on peer-reviewed academic journals and research grants will be
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adequate knowledge of quantitative research methods, as well as a good command of written English. Experience and passion in research topics of palliative and end-of-life care and public health will be
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technical skills in next generation sequencing, including library preparation and bioinformatics analysis. Experience in developing bioinformatics pipeline and maintaining computer server would be
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, fluent in written and spoken English, and competent in basic computer database management. Familiarity or experience with gene sequencing or gene manipulation will be an advantage. The appointee will be
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Chinese (knowledge of spoken Cantonese would be an advantage). A strong background on quantitative research methods and statistical modeling as well as the design and validation of performance assessment