Research Assistant (Centre for Medical Education).

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 optimize 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: CenMED Website.

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 the clinical training environment and is complementing this transition with three-year medical education research to study the datapoints collected to better understand the complexities of the local clinical training environment. We seek an enthusiastic and self-motivated Research Assistant to join our dynamic team, working closely with the Principal Investigator and the Deanery Education Division feedback team to ensure the successful completion of the three-year system rollout. This role requires expertise in design-based methodology to interface effectively with partners and users from two of the three major healthcare clusters, identify systemic barriers, and collate user feedback 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 assistant will be expected to:

• Manage New Feedback System:
  • Maintain user accounts in the system for the campuses in his/her charge.
  • Receive information about clinical posting schedules and student rotations for feedback events creation.
• Interface with Partners and Users: Engage with stakeholders from healthcare clusters to:
  • Onboard posting directors and admins from new pilot sites on how to use the system for feedback events setup, 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.
• Report Design and Setup:
  • Develop and continuously enhance reporting functionalities (with text analysis engine) in our new feedback systems.
  • 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, analysis, 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 operations.

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.
• Be proficient in Microsoft Office; familiarity with Microsoft services and Power BI will be advantageous, or have a willingness to acquire new digital skills.
• Possess strong organizational and time-management skills; some previous research experience will be preferred.

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal inquiries are welcome and should be made to Ms Ng Sue Chia.

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 this job portal.

We regret that only shortlisted candidates will be notified.