As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.
Job Details
This Research Fellow will contribute to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban Climate and Biodiversity in Singapore towards 2030 and Beyond.”
This position requires experience in Geographic Information Systems (GIS) and related fields, with added expertise in ecosystem services assessment, ecological engineering, social sciences, policy making, environmental science, and/or urban environmental issues at the policy–academic interface. This position is ideal for an early- or mid-career researcher with experience in GIS or remote sensing who seeks to apply and expand their expertise in a fast-paced, interdisciplinary research environment.
The successful candidate will work with leading researchers and contribute to cutting-edge research and policy dialogues at the intersection of blue–green infrastructure, tropical urban ecosystem services, and urban resilience (covering themes such as urban flooding, thermal cooling, recreation, and biodiversity). The work includes Local Climate Zone (LCZ) classification and collaboration with Japanese university partners for integrated macro- to micro-scale analysis. As part of understanding the ecosystem services that are involved in Singapore, the successful candidate will also be expected to perform some field-based data collection during the duration of the project.
Key Responsibilities
• Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.
• Identify, simulate, and analyse ecosystem service models using GIS, remote sensing, and field data.
• Manage, process, and analyse ecological and socio-economic datasets to develop and calibrate high-accuracy ecosystem service models.
• Conduct literature reviews and synthesize findings into conceptual frameworks and research designs.
• Support cross–work package integration, particularly in developing tools for blue–green infrastructure policy and decision-making.
• Perform quantitative and qualitative data collection, analysis, and visualization.
• Draft and edit research reports, policy briefs, and academic manuscripts.
• Contribute to project management, workshop organization, and stakeholder or policy dialogues.
• Be involved in regular field work data collection and to perform environmental and biodiversity surveys (fish, birds and insects) as part of a research team.
• To communicate and liaise with any internal and external stakeholders to ensure project deliverables are met.
• Any other ad-hoc duties assigned by Supervisor.
Job Requirements
• PhD in Geography, GIS, Remote Sensing, Environmental Science, Earth Science, or related disciplines.
• Strong working knowledge of GIS platforms (e.g., ArcGIS, QGIS) and spatial data analysis techniques.
• Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping.
• Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python).
• Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS).
• Experience in ecosystem service identification and analysis is highly advantageous.
• Excellent data management, research design, and reporting skills.
• Strong communication and presentation skills in English.
• Highly organized, proactive, and capable of working both independently and within multidisciplinary teams.
Additional Note:
While prior experience in ecosystem service modelling and simulation is not mandatory, it will be considered a strong advantage. Candidates with a solid GIS or remote sensing background who demonstrate interest in applying their skills to ecosystem service assessment are encouraged to apply.
The project team will provide on-the-job training and guidance in ecosystem service modelling tools (e.g., InVEST and related software) to support skill development and ensure effective integration across research tasks.
Key Competencies
• Integrates GIS, remote sensing, and environmental data for spatial modelling.
• Proficient in or able to learn ecosystem service software (e.g., InVEST, ARIES).
• Strong analytical, problem-solving, and data interpretation skills.
• Effective in research design, reporting, and scientific communication.
• Works independently and collaboratively in multidisciplinary teams.
• Demonstrates initiative, adaptability, and sound research ethics.