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atmospheric CO₂ and co-emitted species with inventories to improve them. Develop clustering methods to compare data under similar atmospheric conditions. Analyze spatial and satellite data to assess urban
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; GIS software; spatial analysis and visualization; programming in R, Python, or similar; quantitative data collection and analysis; scientific synthesis and writing. Experience partnering with non
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capped RNA (TLDR-seq): full-length sequencing of capped RNAs (Nucleic Acids Res 2025, doi:10.1093/nar/gkaf240 ) Spatially resolved analysis of microenvironmental gradients in cancer (Science Advances 2024
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areas: GIS software; spatial analysis and visualization; programming in R, Python, or similar; epidemiology; etiology; data communication; systems evaluation; quantitative data collection and analysis
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air quality and emissions measurement instrumentation and systems (e.g., PTR-MS, GC-MS). Strong expertise in advanced statistical, numerical, and spatial data analysis for large-scale datasets is
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and to what extent is an open question. To address this, Rijkswaterstaat initiated the MONS project (https://www.rijkswaterstaat.nl/water/vaarwegenoverzicht/noordzee/onderzoeksprogramma-mons ). In
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Position Description Postdoctoral Associate in Multi-omics analysis Dr. Serpa’s Laboratory - Cyte Department of Population Medicine and Diagnostic Sciences College of Veterinary Medicine Cornell University
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spatial transcriptomics derived from rodent models or human samples. o Oversee data processing, quality control, and computational analysis to ensure high accuracy, reproducibility, and adherence to best
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(derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera traps) can inform spatial planning and decision-making for solar and wind energy
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: Quantitative analysis of experimental data and description of spatial structures in crowds (e.g., Minkowski functionals, Voronoi analyses, clustering methods) Comparison of physical structural analyses with