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maintain algorithms in biomedical image analysis pipelines. Validate algorithm performance on novel datasets. Analyze spatial transcriptomic data. Perform statistical analyses on data extracted form bio
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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of research and academic teaching, contributing to a vibrant environment of research groups focusing on ethnography, materiality, urban/spatial studies, and multimodal/audiovisual research established
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research and academic teaching, contributing to a vibrant environment of research groups focusing on ethnography, materiality, urban/spatial studies, and multimodal/audiovisual research established
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twice weekly. Bard CEP’s GIS course provides students with the fundamentals of using spatial information, conducting spatial analysis, and producing high-quality cartographic products, including storymaps
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proficiency in integrating spatial data into 3D models using sophisticated interpolation techniques. Additionally, the postdoctoral researcher will contribute to transforming mining liabilities into valuable
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⸻ Preferred / Additional Experience Experience in one or more of the following areas will be considered a strong asset: • Flow cytometry (FACS) • RNA-seq / DNA-seq workflows • Single-cell omics • Spatial
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to create analysis‑ready, topology‑correct 3D city models from multi‑modal geospatial data. The position is hosted at the Department of Mathematical Sciences at Chalmers University of Technology and the
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, the Department supports interdisciplinary programs in Urban Studies, International Studies, and Global Health Studies. It is dedicated to tackling urgent global socioenvironmental issues through spatial analysis