10 multiple-sequence-alignment Postdoctoral positions at THE UNIVERSITY OF HONG KONG in Hong Kong
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research MRI techniques and sequences to study patients with stroke and dementia, or at risk of these conditions, in large cohort studies as well as randomized controlled trials Perform other duties as
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(e.g. Linux, R programming) is essential. The appointees will need to perform data analysis of single cell RNA-sequencing, transcriptomics data, Nanopore long read sequencing analysis and/or
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in psychiatry research will be preferred. The appointee will work on multiple projects on psychiatry research particularly focusing on MRI imaging and neuroscience. The appointee will work in a
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on multiple projects on psychiatry research particularly focusing on MRI imaging and neuroscience. The appointee will work in a flexible environment, and have a chance to collaborate with health science
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possess a Ph.D. degree in Nursing, Public Health, Social Sciences, Social Work, Statistics or health-related disciplines, with multiple years of relevant experience. They should demonstrate strong
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at least one programming language (e.g., R, Python, C, or C++). The candidate should have strong expertise in at least one of the following thematic areas (expertise in multiple is a plus, but not required
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or health-related disciplines, with multiple years of relevant experience. They should demonstrate strong competency in qualitative and quantitative data analysis and have a good command of written and
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at least one of the following thematic areas (expertise in multiple is a plus, but not required): Multi-omics & Single-cell Analysis: Processing and interpretation of multi-omics and single-cell datasets
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analysing large scale quantitative research using advanced statistical methods such as multiple linear regression, mediation analysis, multilevel modelling, and latent variable models. Strong organizational
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
for technology-enhanced learning and pedagogical innovation is crucial. Preference will be given to those with expertise in innovative methods of assessment and/or advanced statistical methods, such as multiple