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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary
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tasks. Key Competencies Integrates GIS, remote sensing, and environmental data for spatial modelling. Proficient in or able to learn ecosystem service software (e.g., InVEST, ARIES). Strong analytical
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important jeu de données préliminaires (scRNA-seq de >120 000 cellules, transcriptomique spatiale, cytométrie spectrale), le projet s'articule autour de trois objectifs principaux : 1-Caractériser la
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genomic approaches is to explore clinically relevant aspects of brain tumor biology. We pursue this goal using patient samples profiling, investigating temporal and intra-tumoral/spatial heterogeneity as
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background in multivariate statistical analyses (e.g. R or comparable software) • Proven experience in GIS-based spatial analyses • Experience in species distribution modelling • Track record of peer
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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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French and English; • Motivation, autonomy, curiosity, rigor, and the ability to communicate and interact with a diverse audience. Experience in species modeling, machine learning, or spatial analysis will
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at its institute Senckenberg am Meer in Wihelmshaven, starting as of June 2026: Researcher (m/f/d) for Marine Benthic Ecology and Spatial Modelling (CONMAR-Habitat) (full time / part-time options available
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and implant models Histology, advanced microscopy, and micro-computed tomography Spatial transcriptomics as well as molecular and bioinformatic analyses The candidate will work in a highly
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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