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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 1 day ago
intelligence is growing at a fast pace, the bulk of the world's computing power remains targeted at modeling and predicting physical phenomena, such as climate models, weather forecasting, or nuclear physics
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the TME are relevant to tumour evolution and patient survival outcomes [2-4]. This PhD project will seek to investigate the prognostic value of spatial immunophenotypes in lung cancer combining high-plex
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approaches. The PhD will develop and apply optimization-based energy system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical
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, regeneration and cancer with emphasis of finding new tumour-specific targets. Her lab combines genetically engineered mouse models, patient-derived organoids, and advanced genomic tools to investigate how Wnt
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microscopy, spatial transcriptomics and in vitro and in vivo models to study brain tumor cell-cell interactions and the organization of the cancer ecosystem. We strive for highly collaborative and inclusive
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for therapeutic intervention. This PhD project will leverage large-scale single-cell RNA-seq and spatial transcriptomics datasets from infection biology to develop models, including transformer-/graph-based models
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are of interest. The primary objective of this PhD project is to develop adaptive statistical models for marked spatial and spatio-temporal point processes. Many real-world systems exhibit substantial spatial
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PhD degrees Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5243-HELOUR-075/Default.aspx Work Location(s) Number of offers available1Company/InstituteGéosciences
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the molecular signatures of proteostasis loss and identify early markers of proteostatic failure. The role combines wet-lab spatial biology with computational approaches. You will work across models and scales
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conditions. However, current global climate models (GCMs) lack the spatial resolution to capture these processes, while high-resolution regional models remain too computationally expensive for large ensemble