Urban Analytics Research Engineer

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

National University of Singapore (NUS) invites applications for a Research Engineer/Assistant in Urban Analytics & Data Science. Based at NUS Cities, you will contribute to the CA-ACM project, advancing data-driven understanding of built environments and active living.

You will work with a multidisciplinary team and apply Python, ML, and GIS skills to develop models, visualisations, and research outputs for academic dissemination.

Qualifications

• Master's or Bachelor's degree in a related field.
• Proficiency in Python and ML libraries.
• Strong grounding in statistics and applied mathematics.
• Experience with spatiotemporal data or geospatial analysis is a plus.
• Clear written and verbal communication skills.

Responsibilities

• Collaborate with the Quantitative Research Fellow to advance data science and modelling components.
• Hands-on role with shifting priorities as research evolves.
• Build ML models and quantitative methods for activity sequences and mobility patterns.
• Process and visualise spatiotemporal datasets using Python and GIS tools.
• Develop software components to support archetype classification and simulation.
• Prepare reports, visualisations, dashboards, and manuscripts for diverse audiences.

Skills

Clear written and verbal communication

Interdisciplinary collaboration

Flexible across tasks

Strong attention to detail

Education

Master's or Bachelor's degree in CS/Data Science/Urban Analytics/Geoinformatics/Geography

Tools

Python

ML libraries (scikit-learn, PyTorch, TensorFlow)

Job description

National University of Singapore (NUS) invites applications for a Research Engineer/Assistant in Urban Analytics & Data Science. Based at NUS Cities, you will contribute to the CA-ACM project, advancing data-driven understanding of built environments and active living.

You will work with a multidisciplinary team and apply Python, ML, and GIS skills to develop models, visualisations, and research outputs for academic dissemination.