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great deal of optimization of conjugation conditions. The second aspect of the thesis will aim to reveal the genetic potential of these two strains by analyzing the multi-omic data already obtained
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the world and there is an urgent need to have better prognosis and predictive biomarkers, in order to improve the optimal care of these patients. Many existing therapies lead to an improvement of the overal
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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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of patients treated with immune-checkpoints inhibitors. Our final clinical goals are to help to generate new data-driven tumor response criteria, specifically adapted to immunotherapy, so as to optimize
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the existing highly optimized numerical simulation codes. The PDI Data Interface code coupling library is designed to fulfill this goal. The open-source PDI Data Interface library is designed and developed