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Biology, Immunology, or a related discipline. Experience in cancer research using various animal tumor models would be an advantage. The appointee will work together with a research and development team
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on protein modeling and de-novo protein design. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. The University
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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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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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(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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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
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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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Language Models (LLMs). Development and validation of personalized AI models for early diagnostics and risk stratification of progression risks among patients with chronic hepatitis B infection
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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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statistical modeling as well as the design and validation of performance assessment and psychometric instruments is mandatory. Familiarity with mixed-methods and/or intervention research for youths/vulnerable