Research Assistant (Geospatial And Urban Analytics) - Cities Foresight Lab (Cfl)

Research Assistant (Geospatial and Urban Analytics) – Cities Foresight Lab (CFL)

National University of Singapore – Queenstown

The National University of Singapore is the national research university of Singapore.

Founded in

• as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore.

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.

Responsibilities

Prototype and implement ML algorithms and quantitative models, with a focus on activity and mobility sequences.

Independently develop, test, and iterate model structures, taking initiative to translate urban behavioral theory into data-driven logic.

Clean, label, and visualize spatiotemporal mobility and built environment data with GIS tools (e.g., QGIS, GeoPandas, PostGIS).

Collaborate with an interdisciplinary team to co-design and build a framework for resident archetyping, incorporating dimensions including lifestyle, physical activity, and environmental exposure.

Develop software for data-driven archetyping, using object-oriented programming to model archetype classes and attributes for downstream simulation.

Apply unsupervised learning and rule-based methods to classify movement, demographic and health data.

Develop and evaluate behavioral response models in simulations to test how archetypes respond to interventions.

Conduct behavioral simulations and visualize outputs through maps, dashboards, and policy-facing summaries.

Prepare academic outputs, including abstracts, posters, reports, and journal manuscripts.

Present research findings to both academic and applied audiences and actively contribute feedback to the broader research team.

Qualifications

Master's degree in Computer Science, Data Science, Urban Analytics, Geoinformatics, Geography, or a related field.

Proficiency in Python and ML libraries (e.g., scikit-learn, XGBoost, PyTorch, or TensorFlow).

Skillset : statistics / probabilities / applied math, coding and prototyping; prior experience working with sequence data (trip chains) is highly preferred, and population data is a plus; attention to detail.

Experience with temporal or spatial behaviour modelling is preferred.

Understanding of sequence modelling or spatial ML methods is a plus.

Strong background and expertise in at least one of : spatiotemporal data analysis, activity chain or mobility modelling, machine learning for urban applications, geospatial analysis using GIS tools, or urban informatics.

Experience working in interdisciplinary research teams and collaborating across diverse fields.

Strong quantitative or qualitative research skills.

Excellent written and verbal communication skills.

Excellent interpersonal skills.

Highly motivated, independent and able to work in a dynamic environment.

Application Procedure

Interested applicants should submit a dossier consisting of the following :

A cover letter (maximum 3 pages)

An up-to-date CV

A statement describing research trajectory, interests and career ambitions

Contact details for three referees (only shortlisted applicants will be invited to submit reference letters)

The anticipated start date for the position is 31 December

We will begin evaluating candidates immediately, but the position will remain open until a suitable candidate is found.

Email applications and further enquiries should be sent to

Additional Information

Location : Kent Ridge Campus

Organization : College of Design and Engineering

Department : Architecture

Employee Referral Eligible : No

Job Requisition ID : #J-