The Centre for Nature-based Climate Solutions is a research centre at the National University of Singapore (NUS). CNCS is a focal point for world-class research, thought leadership and education on nature-based solutions for climate mitigation and adaptation in the Asia-Pacific region. It brings together an interdisciplinary group of researchers to produce policy relevant science on natural climate solutions, and build capacity in academic, government and corporate sectors – for the overarching goal of achieving a carbon-neutral economy and stable global climate.
The Centre is actively searching for a Research Assistant to support the Centre in implementing its research programmes and projects.
The main responsibilities of the position include:
• Support the development of policy-relevant, multidisciplinary, and impactful research on nature-based solutions for climate change mitigation and adaptation in natural and/or urban environments, integrating remote sensing and field data
• Collaborate with other researchers as an effective team member
• Support field work, data collection, and data analysis
• Provide general administrative support on research-related matters
• Contribute to the preparation of research manuscripts and reports
Qualifications / Discipline:
• Bachelor’s degree in natural science, climate science, geography, data science, engineering, or related field
• Experience in handling large-scale geospatial data, and in conducting geospatial analysis and modelling
• Experience in employing statistical computing and data visualisation tools, and in coding/scripting using R and/or Python programming languages
• Strong organisational and problem-solving skills, including attention to detail
• Highly self-motivated, independent, and a team player
• Willing to work flexible hours and to take on extra duties as required
• Experience in conducting and/or organising field surveys (e.g., forest inventory, biodiversity census) (preferred)
• Familiarity with processing and analysis of remote sensing data (e.g., optical, LiDAR, SAR) (preferred)
• Experience with implementing machine/deep learning approaches, and/or artificial intelligence projects (preferred)
• Previous publications in peer reviewed journals (preferred)
To apply, please send your cover letter and CV to firstname.lastname@example.org with the subject “Application for Research Assistant".
Only shortlisted candidates will be contacted.