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uses cutting-edge techniques including single-cell and spatial transcriptomics, proteomics, super-resolution microscopy, in vivo tracking, mouse models, and human patient tissues and iPS-derived cells
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on the development of a virtual tissue model bridging cell-cell communication and gene-gene interactions by exploiting spatial transcriptomics data and network-theoretic approaches. Contract start date : May 1st 2026
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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of offers available1Company/InstituteLaboratoire "Atmosphères et Observations Spatiales"CountryFranceCityPARIS 05 Contact City PARIS 05 Website http://www.latmos.ipsl.fr STATUS: EXPIRED X (formerly Twitter
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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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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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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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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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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