Research Associate (Environmental Analytics)
The successful applicant will be part of the interdisciplinary project on “Assessment of Urban Ecosystem Services in Residential Neighbourhoods in Singapore” from Jan to 31 Dec 2024. The position involves work closely with the Principal Investigators, Research Fellow and other members of the team to consolidate and publish the final outputs for the project.
The project is a partnership between the National University of Singapore and the Singapore Housing Development Board. It is funded through the Ministry of National Development and the National Research Foundation, under the Cities of Tomorrow (CoT) Research and Development Programme. The project develops monitoring protocols for environmental quality that can be upscaled to Singapore’s public housing estates and beyond. It involves the use of remotely-sensed data (e.g. satellite imagery) and the deployment of networked “Internet of Things” (IoT) sensors.
The main responsibilities of the position include:
- Conduct literature reviews and write scientific manuscripts to document and share project findings in academic journals
- Collaborate with other team members to finalise monitoring protocols and develop a composite index for environmental monitoring (e.g., soil/water quality recreation, visual quality, thermal comfort, noise abatement)
- Present results during progress updates with stakeholders
- Support the team in research and administrative functions (e.g. procurement, permits, etc.)
- Master’s degree in physical or human geography, environmental science or related disciplines with at least 2 years’ relevant work experience, and good knowledge, skills and expertise in relevant field.
- Evidence of excellent writing and communication skills (e.g., prior publications, academic papers)
- Proficiency in open-source scripting languages (e.g. R or Python) would be advantageous
- Experience in environmental modelling (e.g. thermal comfort, hydrology), Geographic Information Systems (GIS) or remote sensing would be advantageous
- Good understanding of statistics
- Good time management and attention to detail
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Architecture
Employee Referral Eligible: No
Job requisition ID : 22154