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Postdoc: Hybrid Geospatial Modelling and Scenario Development of Carbon Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Carbon Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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Postdoc: Hybrid Geospatial Modelling and Scenario Development of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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Postdoc: Geospatial AI Modelling & Uncertainty Quantification of Biomass Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application deadline
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We are seeking a Postdoctoral Researcher in Geospatial Urban Big Data to support the analysis of urban dynamics and decision-making in territorial planning. The candidate must be proficient in GIS
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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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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
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and geospatial datasets. The All-Island Climate and Biodiversity Research Network (AICBRN) brings together researchers from a wide range of disciplines across the island of Ireland to develop a large
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 28 minutes 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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and outstanding education are interlinked and equally valued. We are seeking a Senior Post-Doctoral Researcher to join the Geospatial Machine Learning (Geo-ML) project in the National Centre