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closely related discipline. At least 5 years of relevant research experience in agricultural data analytics, remote sensing, machine learning, spatial data analysis, sensor systems, or related areas
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. The successful candidate will provide lab-based functional validation of scRNA-seq and spatial transcriptomic findings, translating these into clinically relevant therapeutic targets. The role offers
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, R, MATLAB) for data processing and analysis. - Experience in statistical processing of spatial and temporal data. 4) Instrumentation and metrology: - Knowledge of sensors and measurement instruments
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: Experience with georeferencing and geoprocessing tools applied to urban studies, including the organization, processing, analysis, and spatial representation of data. Strong academic track record, with
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at the intersection of environmental economics, spatial analysis, and social-ecological systems, the Postdoctoral Researcher will lead the development of an inventory and spatial database of ecosystem services impacted
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develop next-generation computational approaches to understand cellular and tissue biology from single-cell, spatial, imaging, and multimodal molecular data. You will develop models that capture cellular
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geoinformatics and spatial data science, including demonstrated knowledge of GIS, spatial analysis, spatial modelling, and GeoAI. Experience and expertise in WebGIS development, familiar with the core technologies
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, genomics, or computational analysis of high-dimensional datasets. Experience with one or more of the following: Flow cytometry Single-cell sequencing Spatial transcriptomics Multiplex imaging Bioinformatics
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, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work with heterogeneous geological, hydrogeological and monitoring datasets and to connect
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 16 hours ago
forest mapping toward temporally resolved reconstruction and prediction of forest-state transitions. The project will leverage Prithvi-EO to extract spectral, spatial, and temporal information from Landsat