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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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of preclinical murine model of melanoma responsive or not to ICI. Specific objectives and methods The specific objectives of the M2 are: 1°) To identify which DC population undergo dynamic changes during ICI
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access to the unobserved values, and therefore, cannot compute this error. The goal of this postdoc will be to develop a direct method, based on self- supervised learning. The closest related works are two
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on heuristics, approximation algorithms, and optimization techniques to generate practical solutions that only reach local minima. Some common approaches include: (1) Iterative refinement methods that improve
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a complex and highly technical environment, OR safety requires the simultaneous management of numerous flows (material resources, human resources, technical environment, etc.) to ensure smooth
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redefinition of behavioral features or pose challenges in their detection. The projects To address these challenges, we propose developing a Bayesian Program Synthesis (BPS) methodology for generating synthetic
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. Côte d’Azur & INRIA), will be focused on the development and the understanding of deep latent variables models for unsupervised learning with massive heterogenous data. Although deep learning methods and
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the understanding of deep latent variables models for unsupervised learning with massive and evolving heterogenous data. Although deep learning methods and their statistical extensions, the deep latent
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enabling trustworthy AI adoption through methods and tools for compliance, readiness, and performance evaluation. In the field of Smart Cities, we lead the operations of the CitCom.ai project. CitCom.ai is