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with Simulation-based Inference ), funded by the Multidisciplinary Institute for Artificial Intelligence (MIAI) through an AIforScience Research Chair. ADACSI will develop a multi-probe simulation-based
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Théorique (LAPTh, CNRS/Univ. Savoie Mont Blanc) invites expressions of interest for one or more postdoctoral researcher positions focused on advancing simulation-based Inference (SBI) frameworks for modern
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determines observables of the replication program such as the Mean Replication Timing (MRT) and the Replication Fork Directionality (RFD) profiles. We proposed a strategy to train a neural network to infer
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, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
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collaborations to implement cosmological analyses derived from the observation of Type Ia Supernovae. This work, carried out within the framework of the ANR SCINF project, aims to develop inference methods based