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regularization. In the morpheme group we have proposed model-driven approach (e.g., COL0RME [1]) as well as model-based data-driven approaches (e.g., GANs [2] or Plug& Play [3]). A different and increasingly
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over the course of the project. References: - Deneu B et al (2021) Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. PLoS Comput
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on the distribution of m6A in different cellular fractions (nucleus, cytosol, polysomes, untranslated RNA) and in viral particles, in order to link these modifications to translation efficiency, localization, and
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28 Aug 2025 Job Information Organisation/Company CNRS Department Laboratoire d'informatique de modélisation et d'optimisation des systèmes Research Field Computer science Mathematics » Algorithms
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD is part of the future JET2SB
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Operando and in situ techniques are becoming mandatory
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will work at the
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
21 Aug 2025 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
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the following two scientific challenges. The first scientific challenge to address is how to effectively fuse the latent space of LiDAR-based models with VLM. This is challenging due to the difference between