67 software-engineering-model-driven-engineering-phd-position Postdoctoral positions in Hong Kong
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Ref.: 533551 Work type: Full-time Department: Faculty of Social Sciences
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, with the possibility of renewal subject to funding availability and satisfactory performance. Applicants should possess a PhD or Master's degree in Nursing, Social Sciences (including Psychology, Social
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, attentive to details, and able to work independently and in collaboration with a multidisciplinary team. Knowledge of multilevel modelling and other statistical methods for longitudinal data analysis
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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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in statistical software (e.g., SPSS, Jamovi, or R), as well as MS Excel and Chinese typing. Experience in the implementation of community or educational research projects will be an advantage. What We
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should possess: A PhD in Biomedical Sciences, Biostatistics, Nursing, or related disciplines; or a Bachelor’s degree in a relevant field with at least 3 years of biomedical research or clinical experience
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develop and pursue a coherent research agenda The ability to develop a body of high-quality publications in scholarly journals with global impact Proficiency in statistical software packages, including R
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or social sciences, demonstrated through relevant experience or coursework. Proficiency in statistical software such as Stata, R, or other relevant tools to facilitate data analysis and interpretation
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Post-doctoral Fellow / Senior Research Assistant (Holding the Functional Title of Senior Psychology)
in statistical software (e.g., SPSS, Jamovi, or R), as well as MS Excel and Chinese typing. Experience in the implementation of community or educational research projects will be an advantage. What We
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promotion subject to funding availability and satisfactory performance. This position is primarily computational/dry-lab. The successful candidate will work closely with our wet-lab team to address key