Research Fellow (Urban climate modelling) 1

National University of Singapore; Singapore; On-site; SGD 20,000 - 60,000; Full time

Job summary

A leading educational institution in Singapore is looking for a full-time Post-doctoral researcher to work on Computational Fluid Dynamics (CFD) simulations focusing on the urban wind and thermal environment. This role involves conducting simulations, publishing research, and presenting findings. Candidates must have a relevant Ph.D. and experience with CFD modelling tools. The position starts in June 2025 and emphasizes both independent work and coordination with project stakeholders.

Qualifications

• Ph.D. degree in a relevant field majoring in Computational Fluid Dynamics (CFD).
• Knowledgeable in CFD modelling.
• Experience in using environmental simulation tools.

Responsibilities

• Conduct multi-scale multi-physics CFD modelling.
• Coordinate and present project updates.
• Publish findings in academic journals.

Skills

CFD modelling

Environmental simulation tools (ANSYS FLUENT, OpenFOAM)

Time management

Publication track record

Programming (Python, R, C, Java)

Education

Ph.D. in Mechanical Engineering, Fluid Dynamics, Atmospheric Sciences, Urban Climate, Architecture Engineering, Building Science

Job description

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

We are looking for a full time Post-doctoral researcher to work on Computational Fluid Dynamics (CFD) simulation in the urban wind and thermal environment project. Position is commencing in June 2025. This posting will remain open until a suitable candidate has been found.

PROJECT

This project, jointly supported by the Urban Redevelopment Authority (URA) and National Parks Board (NParks), aims to advance our understanding of the urban wind and thermal environment within Singapore’s dense cityscape. By deploying high-resolution Doppler LiDAR systems and IoT-based weather stations, the study captures detailed vertical and horizontal wind profiles, temperature, and humidity data within the urban canopy layer. Focusing on selected urban districts such as Jurong and CBD, the project integrates comprehensive datasets—including building morphology from URA and greenery inventories from NParks—to support neighbourhood-scale simulations using the Open Foam and urbanMicroclimateFoam CFD models. These simulations evaluate how urban form, vegetation, and ventilation corridors influence microclimate dynamics and thermal stress under various weather scenarios. The outcomes will directly inform urban planning and design guidelines by identifying effective cooling strategies, enhancing wind permeability, and supporting data-driven decisions for resilient, climate-adaptive urban development in Singapore.

Key Responsibilities

• Conduct multi-scale multi-physics CFD modelling, e.g. simulation of thermal environment, urban greenery, airflow movement and air pollutant transmission, at district and neighbourhood scales;
• Coordinate, prepare and present project updates to the project PI and funding agency on a regular basis;
• Publish the research findings on top-tier academic journals and local/international conferences;
• Assist with project management tasks
• Prepare research proposals;
• Monitor and keep up to date the latest technology and trend in related areas;
• Organize, and assist technical workshops, networking events and conferences (local and overseas).

Qualifications

• Candidate must have a relevant Ph.D. degree in Mechanical Engineering, Fluid Dynamics, Atmospheric Sciences, Urban Climate, Architecture Engineering, Building Science, or related fields majoring in Computational Fluids Dynamics (CFD);
• Well informed and knowledgeable in CFD modelling;
• Highly experienced in using environmental simulation tools, such as ANSYS FLUENT, OpenFOAM or other similar programs;
• Highly motivated individual with capacity to work independently.
• Good time management and planning;
• Good publication track record;
• Some knowledge of Building Energy Modelling, GIS and programming language (Python, R, C, Java) is an advantage.