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Field
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://www.esa.int/ Field(s) of activity/research for the traineeship This fellowship aims to advance the development and application of geospatial foundation models tailored to multimodal and multiscale EO datasets
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At the Technical Faculty of IT and Design of the Department of Sustainability and Planning, Copenhagen, a position as Postdoctoral researcher in Geospatial Machine Learning for Predicting Land Use
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terrain and vegetation structural modelling. Relevant knowledge and experience in development of automated processing methods and workflows for environmental and geospatial data is also essential. About
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conditions Perform modeling and data analysis using coding tools and geospatial data Under the guidance of the mentors, the participant will have the opportunity to develop and conduct in planta experiments
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physical location of this position will be at the Copenhagen campus of Aalborg University. Job Description This position is part of the cross-disciplinary DK-Future project – Probabilistic Geospatial Machine
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 37 minutes ago
publications or manuscripts in preparation. · Demonstrated experience applying deep learning techniques in geospatial or spatial data analysis (required). · Experience with generative AI models (e.g., diffusion
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restoration measures. Prioritisation and optimisation of land for biodiversity, relative to other societal challenges, in particular climate change. Geospatial analyses of past and current land use patterns
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Preferred Qualifications: Experience working with Medicare data or other large administrative data sets Experience designing and implementing randomized controlled trials in the field Geospatial skills
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
across diverse landscapes. To achieve this, we will first create a comprehensive, multi-modal data repository by integrating diverse streams of satellite, meteorological, and geospatial data, which
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent