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In cancer as well as chronic infections, T cells are exposed to persistent antigens and acquire a dysfunctional gene expression program which includes high expression of the inhibitory receptor
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within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies
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, ranging from biological to clinical features. The integration of such heterogeneous information within a coherent computational model is currently challenging, due to the typical large dimension and
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) models. Little attention has been paid to other models like graph NNs (GNNs) or PCA. Among the few existing works in the literature, [2] proposes an FL algorithm to compute PCA in a DP fashion, but the
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machine learning or theoretical biophysics or computer science Conditions. Postdoc position funded by Centre Inria at Université Côte d’Azur, France. The position is located in Sophia-Antipolis, French
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anticipate risks by integrating all human, technical, and organizational factors into a dynamic model of the OR. This project will be developed within the ICARE team (Artificial Intelligence, Computer