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initiation. To this end, researchers are focusing on the development of new data-driven approaches integrating imaging information and patient physiological characteristics to improve the simulation and
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, considering the complex morphological and biological evolutive patterns of tumor lesions after immunotherapy initiation. To this end, researchers are focusing on the development of new data-driven approaches
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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 their career developing state-of-the-art statistical and mathematical methods to analyze epidemic data, with the aim to increase our understanding of how pathogens spread in populations, assess the impact of
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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announced shortly thereafter. The position can start as early as January 2026. Informal requests for information can be sent to application@bricbordeaux.com with “Information Research Chair” as the subject.
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care and patient-based data to the broader research ecosystem in the heart of Europe. The institute is committed to expanding its AI-driven translational and clinical research and it has formed a
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reconstructing the super-resolved image is formalized as an inverse problem which is regularized by introducing suitable sparsity constraint. In our team, we have recently proposed both model-based and data-driven
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train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some