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single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell type, developmental stage, treatment) to build tissue- and context-specific co-regulation networks
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, integration, and validation for environmental and forest monitoring. Familiarity with remote sensing, cartography, and spatial data analysis using specialized software and tools will be considered a significant
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sensing techniques. The ultimate goal is to establish a framework for spatially extensive monitoring of European beech vitality under drought stress in Germany and Central Europe. This project offers
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dashboards that support TASKAR Center for Accessibility (TCAT) and the Transportation Data Exchange’s public-facing and internal initiatives. This role is central to transforming complex spatial datasets
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acquisition in experiments assessing pO2 in encapsulated devices • Develop pipelines for data analysis • Implement and optimize novel pO2 imaging using radiofrequency (RF) spatial-encoding 10% Office Admin
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) government, industry, and local NGO’s. Your main contribution will be the development of a spatially explicit agent-based model of the society of the Metropolitan Region of Amsterdam, simulating circular
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modelling in transdisciplinary processes in order to examine ecological and socio-spatial change, existing biodiversity governance regimes and develop multispecies ethnographies to better understand
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respond to diverse mechanical cues from their environment, including adhesion, stiffness, tension, shear, pressure, and confinement. These cues are integrated across wide spatial and temporal scales, from
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expertise in cell culture and mouse studies. As the work involves the analysis of spatial transcriptomic data, basic expertise in computational biology, with experience in R and/or Python will be beneficial
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Internal Number: JR91931 Scheduled Hours Empty heading 40 Position Summary Empty heading Performs data management and/or data analysis for investigators using statistical packages. Assists investigators in