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, Electrical and Electronics Engineering, Earth Sciences, Remote Sensing, and Artificial Intelligence are also well-suited. (More details on PhD requirements can be found at: https://nusgs.nus.edu.sg
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sciences discipline such as oceanography, remote sensing, or meteorology. • Excellent data management and computing skills. • The ability to engage with and work with a wide variety of international
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appointment and potentially renewable based on performance and funding availability. Key Responsibilities: Develop remote-sensing and geospatial datasets for monitoring land-use change and environmental systems
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this role, you will have: A completed PhD or master’s degree in a relevant discipline, together with relevant research experience. Strong knowledge and understanding of Aboriginal cultures and demonstrated
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, and geospatial decision-support tools using ecological surveys, remote sensing, and airborne LiDAR data. The position offers opportunities to collaborate with government agencies, industry partners, and
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energy for tropical forests. Analyze complex datasets with the NGEE-Tropics data team, including eddy covariance, forest census, plant ecophysiology, remote sensing, land use/land cover change Investigate
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₃ emissions affect peatland ecosystems across the island. The successful candidate will lead research integrating remote sensing, fieldwork, laboratory analysis, and geospatial methods, including GIS and
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Environmental and Remote Sensing Center (NERSC, project leaders), and researchers from ETH-Zürich in Switzerland are international collab-orators. The primary research tool in the project is the Norwegian Earth
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, or equivalent research outputs Required Education PhD in hydrology, civil or environmental engineering, water resources, geography, environmental science, agricultural engineering, remote sensing, or a closely
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on the design and development of mechanically intelligent surgical tools that simplify surgical motions and incorporate image sensing. These tools will be integrated with robotic platforms and machine learning