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Field
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• Integration of physiological and biochemical data with advanced phenotyping approaches (e.g. ther-mal imaging) • Statistical analysis and interpretation of multi-factorial datasets • Active collaboration with
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tools, clinical decision support, and medical imaging applications, are typically categorized as high risk, requiring strong oversight and comprehensive governance. Yet even with clear legal categories
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Technology, Mathematics and Statistics, and Computer Science. More about the position Modern diffusion models underpin state-of-the-art generative AI for images and continuous data, yet principled diffusion
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translate into concrete health outcomes. The BRANCH project wants to change that. By combining conceptual work on green space typologies, advanced geospatial analytics, AI-based image analysis, citizen
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to imaging, modeling, data, and exploitation. Together, they form a vibrant interdisciplinary research ecosystem. We are seeking a PhD student in the research area D - Energy Materials - sustainable aqueous
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, laboratory work, GIS analysis and programming. Work context The proposed thesis is part of work package 2 of the ANR FaSiRé (Archeo-seismicity) project, led by C. Perrin. The work will involve: - image
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aim to investigate the paradigm of explainable AI (i.e. XAI), especially with reference to its interesting facet of commonsense knowledge (CSK). As an application area to highlight the importance
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process, modification of the microenvironment components, and integration with state-of-the-art research technologies such as high- and super-resolution microscopy, quantitative image analysis, spatial
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be the driving force behind the design, construction, and experimental validation of a next-generation magnetocaloric heat pump prototype, a technology poised to revolutionize the market and contribute
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-derived samples for detailed phenotyping of sperm flagella and motile cilia, ultrastructural analysis, and assessment of flagellar/ciliary motility Analysing multi-omics, imaging, and functional datasets