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and quantitative models. Documented capabilities in programming like Python, R, SQL, or Julia. Proficient in Excel and PowerPoint. Preferred Qualifications Geospatial modeling and analysis is a
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Proficiency in Python for geospatial data handling, model workflows, and scientific computing Strong communication skills and enthusiasm for interagency scientific research Application Requirements A complete
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strategies. • Work at the intersection of physics and AI, with an emphasis on geospatial computational modelling. • Collaborate with domain experts and (where relevant) operational
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inventory data with geospatial datasets for biomass or carbon modelling. Managing or synthesising large ecological or geospatial datasets. Conducting or organising field surveys (e.g., forest inventory
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contribute to advancing research in Earth system modeling and to improve understanding of interactions among land, water, carbon, energy, atmosphere, ecosystems, and human systems. This is a one-year
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to classify rangeland plant species, and (2) using transfer learning to adapt deep learning models for imagery analysis to varying UAV sensors and conditions. These techniques will allow you to identify and
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modelling and spatial ecology project focused on urban Singapore. Key Responsibilities: The Research Fellow will develop species distribution models, multi-species occupancy models, biodiversity indicators
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potentially belowground) biomass and carbon stocks using field and remote sensing datasets. Conduct geospatial analysis and modelling using large remote sensing datasets, including optical, radar, and LiDAR
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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conducting quantitative data analysis related to hydrologic systems, including statistics, time-series analysis, geospatial analysis, or model calibration and validation Experience using scientific programming