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Research Assistant/Research Associate (Spatial Urban Ecology Modelling)

1-4 Years
SGD 3,300 - 6,600 per month
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  • Posted 17 hours ago
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Job Description

About the School

The Asian School of the Environment (ASE) at Nanyang Technological University is a diverse school focusing on the connections between geosciences, ecology, society and Earth systems. Our approach integrates these disciplines to examine big environmental challenges both in Southeast Asia and globally. We conduct cutting-edge research on topics that include ecology, geohazards, climate change, sea-level rise, environmental sustainability, conservation of environment and biodiversity, and interactions between environment and society. For more information, please visit our website: https://www.ntu.edu.sg/ase

We are seeking a highly motivated Research Assistant/Associate to join a research group led by Asst Prof Zeng Yiwen. The successful candidate will work on a multidisciplinary project focused on urban biodiversity modelling and spatial ecology in Singapore.

Key Responsibilities:

The Research Assistant/Associate will contribute to the development of species distribution models, occupancy models, biodiversity indicators, and geospatial decision-support tools using ecological surveys, remote sensing, airborne LiDAR, and other environmental datasets. The position offers opportunities to work with government agencies, industry partners, and leading researchers while gaining hands-on experience in ecological modelling, spatial analysis, and biodiversity science.

Job Requirements:

  • Bachelor's or Master's degree in Ecology, Environmental Science, Geography, Geospatial Science, Conservation Biology, Data Science, Statistics, Computer Science, or a related field.

  • Experience with quantitative data analysis using R and/or Python.

  • Familiarity with GIS software (e.g., QGIS, ArcGIS) and spatial data analysis.

  • Interest in ecological modelling, biodiversity conservation, remote sensing, or environmental data science.

  • Experience with species distribution models, occupancy models, machine learning, remote sensing, or geospatial analyses is advantageous.

  • Strong analytical, organisational, and communication skills.

  • Entry-level candidates with strong quantitative backgrounds are welcome to apply.

We seek a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit, regardless of age, race, gender, religion, marital status and family responsibilities, or disability.

We regret to inform that only shortlisted candidates will be notified.

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Job ID: 149151753

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Skills:

Machine LearningQgisPythongeospatial analysesRspecies distribution modelsoccupancy modelsRemote SensingGis Softwarespatial data analysisArcgis