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the context of rapid and unprecedented global urbanisation affecting the Baltic region of Europe, conventional approaches to spatial analysis for urban planning and governance are no longer adequate
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candidate for a project applying state-of-the-art high-dimensional single-cell analysis technologies and spatial proteogenomics to dissect interaction networks between immune cells and the tumor
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metastases. spaXio combines cutting-edge methods like spatial multi-omics, 3D tumoroid models, and AI-powered data analysis to uncover how metastatic niches form and how they might be targeted therapeutically
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the consequences of climate change and strengthen the resilience of mountain areas. The thesis will be based on a multidisciplinary approach combining statistical analysis, level-meteorological modeling, and machine
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involved in various growth processes throughout the plant life cycle. Main objectives will be the prediction of GA-binding residues, their validation using molecular analysis, and the screening for novel GA
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/ climate, risk engineering, data & AI (modelling, simulation, decision support), GIS and spatial analysis, analytical chemistry or toxicology, risk economics / management, law & governance, regulation
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating