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faculty members, researchers, research engineers/associates, and doctoral students, working across areas recognised in France and internationally, such as spatial modelling and analysis, health and risk
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-being, social connectivity, and resilience—integrating geospatial and spatial-temporal analysis to assess patterns, accessibility, and environmental exposure. • Collect, analyse, and interpret data using
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computational analyses of single-cell, spatial transcriptomics, and multi-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI
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, including knowledge of AutoCAD and GIS (ArcGIS or QGIS) software; 6. Knowledge of spatial analysis methods; 7. Experience in university teaching; 8. Fluency in Polish—ability to communicate clearly and
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(landscape) ecologist with a broad, interdisciplinary interest with experience in spatial analysis of interactions between land use and biodiversity. Your work includes teaching courses in environmental
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expertise in biostatistics and spatial data analysis. - Expertise in machine learning. - Advanced expertise in signal processing (accelerometric/gyroscopic and acoustic). - Experience writing scientific
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radiation in the 20–40 eV range, corresponding to the expected operating values for the abovEF instrument under development. Analysis of the detector's response serves to optimize the spectrometer's optical
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α-syn and dopaminergic neurons in a midbrain organoid odel. Integrating aged microglia with midbrain organoids will enable analysis of phenomena that recapitulate PD pathology, including α-syn
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in person in São Paulo and involves single-cell and spatial transcriptomics analysis, integration of multi-disease datasets, investigation of cell–cell communication, and the development
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systems, including methods for colloid characterization Spatially resolved surface analysis using interference microscopy and autoradiography Derivation and parameterization of mechanisms Interdisciplinary