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leverage large-scale AI models to: integrate heterogeneous EO data sources, such as satellite, aerial and in-situ data, across spatial and temporal scales; enable zero-shot or few-shot learning for rapid
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the services nature provides to people. The position will combine ecological data analysis with statistical and spatial modeling to quantify chemical impacts across multiple levels of biological
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routinely mapped with a spatial resolution of the order of millimetres, which prevents mapping, for example, defects. Finer spatial resolution could be accessed with near-field techniques. With the aim
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changes to hydrometeorological forcing. Geomorphology, 414, 108383, https://doi.org/10.1016/j.geomorph.2022.108383 Eelsalu, M., Viigand, K., Soomere, T., Parnell, K., 2024a. Systematic analysis
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preprocessing; Integration of geospatial and soil data into databases. Data processing and analysis: Application of geoprocessing and spatial analysis techniques; Development and calibration of predictive models
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description CRSA - Postdoctoral research fellowship: “Developing Advanced Weather Prediction Models for Agricultural
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vivo models, immune–metabolic signaling, flow cytometry, and cell death or redox biology. Experience with single-cell or spatial transcriptomics is highly desirable. Independent yet collaborative
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investigate whether neutrophils can be targeted to enhance immunotherapy efficacy. Current research on neutrophil function in cancer relies heavily on mouse models, which may not accurately reflect human
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to create Temporal and Spatial rescaling of satellite remote sensing data Geospatial Model automation with GeoAI with python script-based independent tools development to use in Models for Culvert
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improvement. Pursue and support grant-funded research through methodological design, analytic strategy, and dissemination. Conduct advanced statistical modeling (regression, multilevel, survival, and causal