Research Fellow

Interested applicants are invited to apply directly at the NUS Career Portal. 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 Community Assets and Activity Chain Modelling (CA-ACM) project is a research study commissioned by the Health Promotion Board to investigate how Singapore's built environment shapes residents' daily activities and lifestyle patterns. The project aims to identify features of the built environment that make active living intuitive and natural; develop composite indicators to measure and rank the attractiveness of different urban settings for various population groups; and uncover how these environmental features influence the type of physical activities people choose to engage in. The project brings together experts in urban studies, data science, public health, and social science research to surface evidence-based insights and design strategies that promote more active living. We seek a motivated and talented Research Fellow to lead the implementation of the CA-ACM project, which investigates how the built environment and community assets shape environmental behaviours, physical activity, and well-being in Singapore. Responsibilities: Lead and coordinate implementation of the research project. Design and execute the geospatial mapping of community assets by integrating data from government, open-source, and community-level sources. Design, implement and refine the framework to evaluate community asset features and their attractiveness to different population groups, applying mixed methods approaches (systematic literature review, Delphi methods, focus group discussions, and ecological momentary assessment) and ethnographic case studies in collaboration with agency partners. Design and implement the surveys and focus group discussions to validate and refine initial archetypes and activity chains derived from big data modelling. Collaborate with Research Assistants (Geospatial and Urban Analytics) and Research Fellow (Data Science/AI) to achieve overall project goals. Publish research findings in top-tier academic journals and present at local and international conferences. Mentor junior research performers and provide active feedback to the team. Coordinate, prepare, and present project updates to PIs, Co-PIs, and the funding agency on a regular basis. Proven experience in preparing and submitting research ethics applications (e.g., IRB approval) and ensuring compliance throughout the project lifecycle. Qualifications Ph.D. in Architecture, Urban Planning/Studies, Physical/Human Geography or related fields. Strong and demonstrable experience in mixed-methods research, including both qualitative approaches (interviews, focus groups, ethnographic case studies, ecological momentary assessment) and quantitative approaches (survey, GIS-based analysis, activity modelling). Deep expertise in qualitative methods (e.g., grounded theory, thematic coding, content coding) with proven track record of publications. Familiarity with quantitative methods (e.g., spatial analysis, statistical modelling) and data analysis is preferred. The candidate must be comfortable with synthesis and interpretation of results derived from quantitative and qualitive approaches, as well as a strong ability to integrate multi-source data (government, open-source, community-level). Strong background and expertise in one or more of the following areas: environmental behaviour studies, built environment and health, urban sociology, community asset evaluation, or urban analytics. Proven track record of research excellence, demonstrated through publications in reputable journals and conferences. Experience working in interdisciplinary research teams, participation in community-engagements, as well as collaboration with government agencies and partners. Excellent project management and organisational skills, with experience coordinating research activities and reporting to multiple stakeholders. Strong communication skills, with the ability to convey complex findings to academic, policy, and practitioner audiences. Ability to work independently and collaboratively in a dynamic research environment. Commitment to research ethics and compliance with institutional approval processes. Application Procedure: Interested applicants should submit a dossier consisting of the following: a cover letter (maximum 3 pages)up-to-date CV a statement describing their research trajectory, interests and career ambitions contact details for four referees (including applicant's main PhD supervisor) (only short-listed applicants will be invited to submit reference letters The anticipated start date for the position is 31 Dec 2025. We will begin evaluating candidates immediately, but the position will remain open until a suitable candidate is found. Further enquiries should be sent to #J-18808-Ljbffr