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students with settled status. This project addresses the pressing challenge of data scarcity in spatial transcriptomics (ST), crucial for advancing cancer research. ST data, revealing spatial and gene
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multidisciplinary environment, the candidate will work on the development of novel methods for analysis of state-of-the-art spatially resolved data. The candidate will explore the landscape of explainable machine
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development of novel methods for analysis of state-of-the-art spatially resolved data.The candidate will explore the landscape of explainable machine-learning and optimization approaches and create novel
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PhD Studentship: How Does Spatial Organisation Impact Host-microbiome Interactions in Human Airways?
The spatial organisation of microbial communities can be influenced by chemical gradients (e.g. metabolite concentrations), physical features (e.g. spatial scale, airflow), and biological factors
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pathomics dedicated to personalized medicine. This innovative and rich approach stems from the explanatory integration of deep learning in computational histopathology as well as spatial transcriptomics
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for the SPADES toolbox. Enhance understanding of the transition towards healthy soils, using spatial planning and design, based on systemic analysis from the spatial planning and design and soil management
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candidate will have the opportunity to interact with the community at the local, Parisian, and European level. The successful candidate will be involved in a collaborative project on spatial orientation
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understudied. Building on novel insights related to TR NK cells from this work, we will address questions related to metabolism and spatial localization of human TR NK cells at steady state in this PhD-student
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biologists, physicists and chemists in industry and academia? Are you interested in developing a new set of tools that can be used to image metals, metabolites and proteins in cells at unprecedented spatial
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Description The thesis encompasses various activities, including the collection and analysis of historical data on extreme "dry" weather events and energy blackouts, the development of methodologies to identify