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Your application will be processed only if you apply via NUS Career Portal.
We regret that only shortlisted candidates will be notified.
Job Description
The National University of Singapore invites applications for Research Assistant for “Medical Education Research on real time teaching and learning data collection and reporting system (BLUE)” in the Centre for Medical Education (CenMED), Yong Loo Lin School of Medicine. The Centre for Medical Education (CenMED) at NUS focuses on promoting professionalism and excellence in medical education through faculty development, educational policy support, and scholarship in teaching and learning. Known for its professional development programs tailored to clinical teachers and its annual Asia Pacific Medical Education Conference (APMEC), CenMED aims to enhance the teaching skills of faculty and optimise student learning. Established in 2002 and expanded in 2014, CenMED is dedicated to creating an educational environment that produces competent, caring medical practitioners. You can find out more about CenMED here: https://medicine.nus.edu.sg/cenmed/index.html
Appointments will be made on an annual contract basis in the first instance, with the possibility of extension up to 31 Oct 2027.
Purpose of the post
The school is transiting out of a legacy student feedback management system into a real-time feedback collection system in clinical training environment and is complementing this transition with three-year medical education research, to study the datapoint collected to better understanding the complexities of the local clinical training environment. We seek an enthusiastic and self-motivated research assistant to join our dynamic team, to be responsible for, and to work closely with the Principal Investigator and the Deanery Education Division feedback team to ensure the successful completion of the 3 year system roll out. This role requires expertise in design-based methodology to interface effectively with partners and users from two of the three major healthcare clusters, to identify systemic barriers, and collate user feedback and use these to refine system setups. The research team will also analyze and gather insights to build AI enabled capabilities using data collected, which can then be used to inform and improve clinical training outcomes.
Main Duties and Responsibilities
The research fellow will be expected to
- Manage new feedback system:Maintain user account in the system for the campuses in his/her charge
Receive information about clinical posting schedule and student rotation for feedback events creation
- Interface with Partners and Users: Engage with stakeholders from healthcare cluster to:Onboard posting directors and admins from new pilot sites on how to use the system for feedback events set up, submit data rectification, and retrieve management reports
Onboard tutors and students on how to participate in the new workflow
Identify limitations and barriers that hinder the rollout of new workflows
- User Feedback/Requirement Gathering:Gather and compile feedback/reporting wishlists from users to inform the core team and vendor for system setup, automation enhancements, and reporting capabilities
Main Duties and Responsibilities
- Report Design and Setup based on user needs and team insights:Develop and continuously enhance reporting functionalities (with text analysis engine) in our new feedback systems and
Develop and continuously enhance reporting functionalities in Power BI
- AI Model Development: By mid to late project phases, contribute to developing, testing, training, and implementing AI models in Microsoft environment to detect, categorize, and manage preemptive measures for data rectifications.
- Report writing and Dissemination:Contribute to literature searches, preparation of reports, anaylsis, research papers, and presentations.
Assist in the dissemination of research findings through various channels, including conferences and publications.
Ensure that by the end of the third year, system setup is properly documented for handover to operation.
Qualifications
The applicant should:
- have a Bachelor’s degree in a relevant field or related disciplines with a background in Social Science, Psychology or Behavioral Science preferably with experience in axial coding;
- be able to work independently and in a team, have an investigative nature, attention to detail and excellent interpersonal, written and verbal communication skills;
- proficient in Microsoft Office, familiarity with Microsoft services and Power BI will be advantageous, or a willingness to acquire new digital skills;
- Strong organizational and time-management skills, with some previous research experience will be preferred.
Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to Ms Ng Sue Chia at [email protected].
Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to the NUS Career Portal.
We regret that only shortlisted candidates will be notified.
