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consequences for essential ecosystem processes. In the framework of the Biodiversity Exploratories (https://www.biodiversity-exploratories.de/en/ ), funded by the German Research Foundation (DFG), the project
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open-source software packages and set up computational pipelines. As a bio-informatics research lab, we publish software packages in Python and R for specific, cutting-edge analysis of large-scale
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or fragments). Practical experience of complex tissue analysis using multistaining techniques and image analysis. Practical experience of analysis of spatial proteomics and/or transcriptomics data. Experience
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multidisciplinary experience in combining integrative computational immunology – data-driven, state-of-the-art single cell resolution and spatial methods, machine learning and kinetic modeling – with integrative
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working knowledge of GIS platforms (e.g., ArcGIS, QGIS) and spatial data analysis techniques. Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping
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Basic and Applied Spatial Analysis Lab (BASAL). The BASAL is located within the Department of Natural Resources and the Environment at the University of New Hampshire. This researcher will work directly
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in applied economic analysis (e.g., causal inference, econometrics, spatial equilibrium modeling). • Experience working with large-scale datasets and interdisciplinary research. • Demonstrated research
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methods for spatial transcriptomics, advanced microscopy, volumetric imaging, neuronal activity mapping, and multimodal data analysis, with an initial focus on neuroscience. To build this interdisciplinary
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experience of quantitative environmental data analysis, including climate data, ecological or forest inventory data, and/or spatial data sets, and skills in statistical analysis and data processing using tools
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methylome sequencing, custom NGS panels, liquid biopsy, and spatial transcriptomics. The primary focus of this position is to help optimize and complete research tasks related to the computational analysis