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situ or even operando (laboratory and Synchrotron), and modeling tools (Monte Carlo, molecular and Brownian dynamics, machine learning), allowing, as often as possible, spatially and temporally resolved
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logistics. A key aspect of the post will be translating complex findings into clear and accessible written, visual and spatial materials, including maps, diagrams, presentations and other publication-ready
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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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architectures for (bio)medical research and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and spatial multi-omics data; AI-based
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colleagues from FBMH. Areas of current research are novel dose delivery methods (FLASH therapy and spatially fractionated), imaging (using prompt photons and proton CT), high throughput radiobiology
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-Lab, we are committed to develop break-through PAT technologies, with novel and advanced imaging performance in terms of spatial resolutions, imaging speed, penetration depth, detection sensitivity, and
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fields: Material Science, thermal simulation, Metallurgy, Solidification of alloys,... School - Location: Centrale Lille Institute Laboratory: LaMcube Web site: http://lamcube.univ-lille.fr/ Name of
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learning, statistical, spatial and temporal modelling approaches to understand mental health need, crisis trajectories, service entry patterns, and system performance across rural, coastal, and small urban
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available1Company/InstituteCentre d'études spatiales de la biosphèreCountryFranceCityTOULOUSEGeofield Contact City TOULOUSE Website https://www.cesbio.cnrs.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn
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, their cross-talk with hepatocytes and ductular reaction (DR) cells, and how these interactions determine regenerative capacity. Using advanced imaging, spatial transcriptomics, and innovative 3D culture systems