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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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be requested to arrange for at least three references, including one from their PhD supervisor/advisor. Review of applications will commence as soon as possible and continue until November 30, 2025
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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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of renewal subject to satisfactory performance. Applicants should have a PhD degree in biological/biomedical sciences or a related discipline. They should be hardworking, self-motivated, and able to work
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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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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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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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of responsibility and commitment. Preference will be given to those with previous research experience in virus-host interaction, influenza viruses and animal models. Eligibility to work in Biosafety
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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