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critical juncture as food insecurity, environmental degradation, a changing climate, and socio-economic disparities threaten its stability and resilience. The RF is expected to use remote sensing
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, computing and/or Earth science Proficiency in remote sensing, geographic information systems, and statistics Proficiency in programming with Python, R, and Google Earth Engine At least 3 years of working
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passion for learning, who would enjoy working with people from a wide range of disciplines – including seismology, geodesy, geology, remote sensing, tectonics, volcanoes, risk, social science and history
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cycle and climate prediction. The RF is expected to use terrestrial biosphere models, Earth system models, remote sensing, and recent developments in ecological theory to simulate and deepen our
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countries in Southeast Asia, that are supported by the EOS Centre for Geohazard Observations, as well as a Remote Sensing Lab (EOS-RS). Computational resources are available through a dedicated cluster and
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in Southeast Asia, that are supported by the EOS Centre for Geohazard Observations, as well as a Remote Sensing Lab (EOS-RS). Computational resources are available through a dedicated cluster and
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The Centre for Remote Imaging, Sensing and Processing (CRISP), in collaboration with NUS Environmental Research Institute (NERI) and Department of Civil and Environmental Engineering (CEE) seeks
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in at least one of Matlab, R and Python. Experience working with terrestrial biosphere models or earth system models. Experience with plant ecophysiology and remote sensing is a plus. Strong numerical