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for academic publications, building research partnerships with local researchers and community partners and stakeholders. We are looking for someone with (1) PhD in Social Work, Geography, Psychology, Policy
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the quality of life for older adults through innovative research and community engagement. Applicants for Post-doctoral Fellow should possess a PhD degree or equivalent in Social Science, Psychology, Public
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ensuring rigorous data integrity. Applicants should possess a PhD or equivalent doctorate in audiology, hearing science, or a related field, combined with proven experience in managing research projects
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-doctoral Fellow should possess a PhD degree or equivalent in Social Science, Psychology, Public Health or other related disciplines with at least 2 years of post-bachelor’s work experience. Previous work
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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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the scientific design, oversight, and execution of the study while managing research staff and ensuring rigorous data integrity. Applicants should possess a PhD or equivalent doctorate in audiology, hearing
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learning. He/she will be responsible for literature review, preparation of assessment materials, liaise with external parties, coordination of research activities, conducting assessments with children and
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visualisation skills, the ability to present abstract concepts in an accessible way to all organisational levels and to acquire new statistical techniques by self-learning. They should be responsible, mature
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of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R. They should
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis