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and erosion processes. Skills in GIS, spatial analysis of large scale data, modelling, remote sensing, and programming (R or Python) are desirable. You work independently, communicate effectively
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; environmental exposures and resilience to heat, flooding, and pollution in cities; geography of emerging diseases; health co-benefits from urban sustainability transitions; GIS, spatial modeling, and data-driven
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and spatial transcriptomics and epigenomics. More details: https://research.pasteur.fr/en/team/cellular-plasticity-in-age-related-pathologies/ Candidate profiles We are seeking highly motivated
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, Doctoral School of Biology, Chemistry and Health (Ecole Doctorale Biologie-Chimie Santé). The EPIMAST project is titled “Respiratory epithelium and mast cells: pathophysiological modeling and identification
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the advantages of the ADS are linked to its subcriticality, this must be ensured under all conditions (normal, incident, or accident). The SPATIAL project aims to develop a reliable method for measuring reactivity
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-trained tool on other image sensors and at different mountain sites presents difficulties. Specifically, generalizing a model trained on a specific site to other sites with different environmental
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constituent une phase électronique caractérisée par une modulation spatiale de la densité électronique présente dans certains matériaux métalliques, souvent liée à l'apparition d'une bande interdite dans le
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 18 days ago
on the study of human tumors through the use of multiple genomic technologies. The methods used include gene expression profiling using bulk RNAseq and scRNAseq, DNAseq, and spatial transcriptomics. The main
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Experience in groundwater modeling. Strong skills and experience with GIS platforms (e.g., ArcGIS, QGIS) and spatial data processing. Skill and experience with machine learning. Have a publication track record
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in urban and territorial systems. The researcher will focus on the design and application of hydrological, and AI-based modelling approaches to address water-related challenges in urban environments