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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 Deep learning models, and in particular large language
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trigger reconstruction architectures for future particle collider experiments, based on deep learning models distributed across multiple hardware processing stages. The mission of this position, based
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. To that aim, both Stein-based bilevel optimization, empirical Bayesian and unsupervised deep learning approaches will be considered. The recruited postdoc researcher will tackle both implementation challenges
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variational models and deep learning techniques. You will implement and validate reconstruction algorithms, ensuring their performance, robustness, and efficiency for clinical application. You will participate
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | about 1 month ago
attention, prediction and learning, as well as the intricate coupling between action and perception. Our research combines (1) cross-species in-vivo observations of brain electrical and neurotransmitter
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on the development of deep learning methods for reconstruction and physics analysis of the ATLAS experiment data. The successful candidate will develop innovative analysis methods for the reconstruction or the physics
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anthropogenic factors using deep learning and vision transformer models, (2) Incorporating past factor trends for more realistic predictions under the non-equilibrium hypothesis, (3) Leveraging transfer learning
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: Verifiable world models. The research will focus on developing a new class of structured, verifiable world models that integrate the flexibility of deep learning with the rigor of formal methods and
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 2 months ago
to motion and respiration. Over the past years, we led several works in this area. Particularly, we developed several deep learning models for the segmentation of SC lesions either from T2 sagittal MRI
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in