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the possibility of renewal, subject to satisfactory performance and funding availability. Applicants should possess a Ph.D. degree in Social Work, Psychology, Statistics, Public Health, or a related discipline
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of renewal subject to satisfactory performance. Applicants should possess a Ph.D. degree in Computer Science, Mathematics, Statistics, computational biology, related disciplines or equivalent. They should be
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or equivalent, with 3 years’ related work experience, or a Ph.D. degree in a relevant discipline; (ii) solid statistical and computing skills; (iii) effective communication skills in both written and
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familiar with health systems, healthcare decision-making processes in Hong Kong or comparable Asian settings; Have proficiency in qualitative data analysis software (e.g., NVivo) and relevant statistical
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into the common data model. Conduct advanced statistical analyses and epidemiological studies on RWD. Collaborate with the Research Coordinators and Project Managers to define analysis plans and ensure data quality
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, Data Science, Statistics, Computer Science, Informatics or related disciplines. Preferably minimum 5 years’ experience in epidemiology, data management, programming and statistics at supervisory level
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proficiency in qualitative data analysis software (e.g., NVivo) and relevant statistical/modelling tools; Show a strong publication record in peer-reviewed journals commensurate with career stage; and Possess
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Psychology, Neuroscience, Cognitive Science or equivalent, with 3 years’ related work experience, or a Ph.D. degree in a relevant discipline; (ii) solid statistical and computing skills; (iii) effective
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, Statistics, computational biology, related disciplines or equivalent. They should be self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese
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) to integrate advanced AI/ML techniques into the RWE generation pipeline. Requirements PhD degree in Epidemiology, Data Science, Statistics, Computer Science, Informatics or related disciplines. Preferably