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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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for managing smart cities. The team has gained substantial experience in machine learning for road traffic monitoring. They are now keen to thoroughly explore the additional opportunities presented by
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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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computational modeling and/or analysis of complex biological systems, integrating state of the art tools such as machine and deep learning approaches. Experience in managing biological databases and statistical
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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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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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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Context and Motivation Bilevel optimization problems, in which one optimization problem is nested within another, arise in a wide range of machine learning settings. Typical examples include