Research Engineer / Assistant (Agentic AI for Sustainable Building and Urban Design)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Engineer-Assistant-%28Agentic-AI-for-Sustainable-Building-and-Urban-Design%29/32668-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Model Development:
. Develop and train surrogate ML models (e.g., neural networks, Gaussian processes, gradient boosting) to emulate computationally intensive building and urban performance simulations - including EnergyPlus (thermal/energy), Radiance/Daysim (daylighting), and CFD tools (airflow/microclimate) - enabling real-time performance feedback within agentic design workflows.
. Design and implement agentic AI workflows for building and urban design tasks, including multi-step reasoning pipelines, tool-calling agents
. Integrate large language models (LLMs) with physics-based simulation tools and parametric design environments (e.g., Rhino/Grasshopper, EnergyPlus, QGIS) to automate and accelerate performance-driven design workflows.

Platform and API Development:
. Build and maintain backend services, APIs, and user-facing interfaces that expose AI research outputs to end users in the architecture, engineering, and construction (AEC) sector contribute to open-source tools and research prototypes developed within the City Syntax Lab.
. Develop and evaluate benchmarks for LLM spatial reasoning in building and urban contexts, contributing to academic research on AI capabilities and limitations in domain-specific design and simulation tasks.

Research & Dissemination:
. Publish research findings and present at academic conferences document tools, experiments, and evaluation results to ensure reproducibility and support knowledge transfer within the lab and to external collaborators.

Job Requirementss

Essential:
. Bachelor's or Master's degree in Computer Science, Software Engineering, Building/Urban Science, Electrical Engineering, Data Science, or a related field.
. Proficiency in software engineering best practices including version control (Git), containerisation (Docker), CI/CD pipelines, and API design experience building and deploying production-ready or near-production applications is strongly preferred.
. Hands-on experience building LLM-powered applications, including prompt engineering, function/tool calling, agentic pipelines
. Strong Python programming skills experience with web frameworks and API development (e.g., FastAPI, Flask) and/or frontend development (React, TypeScript) is advantageous.
. Experience with life-cycle carbon assessment methods and tools.
. Genuine interest in sustainable built environments, climate technology, or smart cities prior exposure to AEC software (e.g., Rhino, Grasshopper, Revit, EnergyPlus) or geospatial tools (QGIS, GIS APIs) is a plus but not required.
. Ability to work in a fast-paced, applied research environment, take ownership of projects, and translate academic research prototypes into functional, deployable tools.
. Strong communication skills and ability to work collaboratively across a multi-disciplinary team spanning AI research, building science, and urban planning.