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Field
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Models (LLM) to query and reason geospatial data. The project aims to develop a pilot decision support systems in collaboration with industry partners. The Postdoctoral Research Fellow will undertake
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geospatial modelling, remote sensing technologies and techniques, and methods of erosion/sediment loss mitigation. You will have a strong mix of research and digital skills, including experience with
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) strong background in quantitative methods, statistics, computer science, geospatial data analysis and modeling; (b) experience in AI and geospatial computer version; (c) advanced skills in scientific
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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
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requires a high level of judgment, scientific initiative, and technical skill in geospatial data processing, as well as the ability to manage multiple deadlines and prioritize tasks. The successful candidate
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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, crop yield). -Familiarity with geospatial data and tools (e.g., GIS, QGIS, Google Earth Engine). -Knowledge of explainable AI (e.g., SHAP, LIME), model interpretation, and/or uncertainty quantification
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Basic proficiency related to geospatial analysis (e.g., ArcGIS, QGIS, Google Earth Engine). Strong oral and written communication skills. Experience working with and managing interdisciplinary research
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: Geospatial technologies and digital twins for action on urban sustainability”. Qualifications Applicants for the Postdoctoral Fellow post should have a doctoral degree or an equivalent qualification and must
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Earth Observation data including Satellite Remote Sensing together with Soil and geospatial datasets. The All-Island Climate and Biodiversity Research Network (AICBRN) brings together researchers from a