The appointee will assist the project leader in the research project - “Advancing the detection of developmental language disorder in children using large language models”, which involves large language models (LLMs), including the development and adaptation of foundation models, the design and implementation of agentic AI systems, and their applications in neurolinguistics, healthcare, digital humanities, and related interdisciplinary areas. He/She will be required to:
The Research Assistant / Research Associate will need to:
(1) take primary responsibility for the day-to-day running of the NUS Health study and, in particular, for maintaining the study sample, including participant retention and engagement, adherence monitoring for wearable device use and daily questionnaire completion, participant communications and administration of the incentive framework, and coordination of the baseline, intervention, and post-intervention assessments;
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Candidates should possess clear Communication skills, including the ability to present findings, prepare concise reports, and collaborate effectively with team members.
Relevant qualifications such as a diploma or degree in science, engineering, data science, or a related field are beneficial.
Attention to detail, strong organizational skills, and the ability to manage multiple tasks and deadlines are important.
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Applicants should submit the following documents in the online application: (1) full curriculum vitae with publications; (2) academic certificates; and (3) contact information of at least two referees.
The University only accepts and considers applications submitted online for the post above via the CUHK career site. For more information and to apply online, please visit http://career.cuhk.edu.hk.
Candidates should possess proficiency with digital tools for research management, such as reference managers, spreadsheets, and collaborative platforms.
Bachelor’s degree or equivalent experience in a relevant field (e.g., science, engineering, social sciences, or related disciplines).
Strong attention to detail, ability to follow research protocols, and commitment to research integrity and reproducibility.
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