Job Description

To support the UrbanHeatMap project, which aims to develop scalable, high-resolution ambient temperature mapping methods by integrating outdoor microclimate measurements, mobile sensing data, satellite-derived land surface temperature, and urban morphology information. The Research Assistant will work closely with Research Fellows and the Principal Investigator in generating high-quality field validation datasets and supporting data-driven urban heat research across selected test-bed sites in Singapore. This role is suitable for candidates interested in urban climate, environmental sensing, outdoor thermal comfort, and data-driven approaches to urban heat mitigation.

Urban Microclimate Measurement and Field Campaigns:
    ·    Contribute to the planning and execution of outdoor microclimate measurement campaigns across selected HDB precincts and test-bed sites, including NUS campus and SIT Punggol Digital District.
    ·    Support the development and implementation of field measurement protocols to ensure data consistency, repeatability, and scientific validity across different sites and measurement periods.
    ·    Ensure that field measurements are properly synchronised with project requirements, including model validation, sensor comparison, and site-level urban heat assessment.

Microclimate Data Processing and Quality Assurance:
    ·    Process and organise datasets collected from stationary, mobile weather stations, drone-related measurements, and other field sensing platforms.
    ·    Conduct data quality assurance and quality control.
    ·    Prepare clean, georeferenced, and well-documented datasets for modelling, validation, and analysis by linking sensor measurements with GPS coordinates, site information, and urban morphology attributes.
    ·    Support analysis and visualisation of microclimate patterns, including temporal trends, spatial variation, site comparisons, and summary statistics.

Research Analysis and Project Deliverables:
    ·    Support the interpretation of field measurement results in relation to urban heat island effects, outdoor thermal comfort, and local urban morphology.
    ·    Assist in preparing figures, tables, maps, technical summaries, and presentation materials for project meetings, reports, and stakeholder updates.
    ·    Contribute to literature reviews and technical documentation related to urban microclimate measurement, environmental sensing, outdoor thermal comfort, and urban heat mitigation.
    ·    Contribute to the preparation of research outputs, technical reports, and academic publications.
    ·    Participate in project meetings and coordinate with internal and external collaborators.

Job Requirements

Essential:
    ·    Bachelor’s or Master’s degree in Computer Science, Urban Building Science, Environmental Science, Atmospheric Science, Urban Studies, Mechanical Engineering, or a related field with strong quantitative and computational components.
    ·    Experience or strong interest in working with environmental, spatial, or time-series datasets.
    ·    Familiarity with urban microclimate dynamics, urban heat island (UHI) effects, and thermal comfort indices (e.g., PET); experience with microclimate simulation tools (e.g., ENVI-met) is advantageous but not required.
    ·    Data processing skills using Python, R, MATLAB, or similar tools.
    ·    Good organisational skills and attention to detail in data management, field documentation, and research workflow.
    ·    Willingness to conduct outdoor fieldwork in Singapore as part of microclimate measurement campaigns.
    ·    Ability to work both independently and collaboratively within a research team.
    ·    Good written and verbal communication skills.

Desirable:
    ·    Experience with environmental sensors, weather stations, thermal comfort instruments, GPS devices, mobile sensing platforms, or other field measurement equipment.
    ·    Experience with microclimate data, meteorological data, spatial data, time-series data, or sensor data quality control.
    ·    Familiarity with GIS tools such as QGIS or ArcGIS would be advantageous.
    ·    Basic Python or R programming experience for data cleaning, visualisation, and quality control would be advantageous.
    ·    Familiarity with urban morphology indicators such as sky view factor, greenery, building density, land use, surface materials, or urban canyon geometry would be advantageous.
    ·    · Prior experience in environmental monitoring, outdoor field measurement campaigns, urban climate research, or thermal comfort studies would be advantageous.