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pool of leukemic cells in sanctuary lymphoid organs leading to transformation in high-grade lymphomas. 3) the elaboration of computational prediction tools of progression and new preclinical models
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advances in machine learning and data-intensive approaches facilitate the search for better or even global minima via evolutionary computations or reinforcement learning. Objectives. The main scientific
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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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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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this technology for capturing and processing the pulse of a city. In particular, in many applications, DAS suffers from the multi-source aliasing problem and low-frequency noise, especially in noisy environments
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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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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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Permanent contract | Belvaux Do you want to contribute to public research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
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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
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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