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, molecular and cell biology, and animal models. Skills in bioinformatics are advantageous. Candidates should be highly motivated and have a track record of publications in international journals. The appointee
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Experience in image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed
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plasticity with a focus on cancer stemness using hepatocellular carcinoma as a model system, that is part of a theme-based collaborative project. For further information, please contact Professor Stephanie Ma
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, and assessing the impact on disease progression. Develop relevant disease models to assess therapeutic efficacy of a specific treatment. Demonstrate understanding of the disease pathology for better
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in longitudinal analyses, multilevel modelling, data visualisation, and state-of-the-art statistical and epidemiological models would be an advantage. The appointees will be primarily responsible
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(e.g., multilevel modelling, structural equation modelling, latent profile analysis, etc.), will be an advantage, as will a strong publication record with internationally recognised journals
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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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of family and mental health are preferred. They should be competent in advanced quantitative analysis (e.g. SEM, multi-level modelling, factor analysis) and experienced in using statistical software (e.g
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oncology-specific NLP models with peer-reviewed publications is preferred. Strong quantitative skills are mandatory, including analysing large-scale databases (e.g., Hospital Authority EHR) using R/STATA/SAS
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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