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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 4 days ago
accurately study the selected algorithms, participate in the development and maintenance of the PEPit (https://pepit.readthedocs.io/ ) and AutoLyap (https://github.com/AutoLyap/AutoLyap/ ) software packages
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20 Dec 2025 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique de Toulouse Research Field Computer science Mathematics » Algorithms Researcher Profile First
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; apply the developed methodology to complex heterostructures The postdoctoral researcher will be recruited within the Chemical Theory and Modelling team (http://www.quanthic.org ) of the Institute
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of autonomous flow reactors for chemical synthesis. The project aims at 1/ developing a new optimization Bayesian algorithm and 2/ improving the process-control software already developed in the team
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to update Frame Analysis by adding visualization repertoires and to develop an analytical framework that will enable political scientists to more systematically integrate the visual approach into various
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 days ago
fields including health, agriculture and ecology, sustainable development. More information, please visit https://team.inria.fr/scool/projects Odalric-Ambrym Maillard is a permanent researcher at Inria. He
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 1 month ago
models. The project's central goal is to move beyond algorithm-independent bounds and develop rigorous theory that unpacks the generalisation properties inherent to the training and sampling processes. A
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explainable. Our team builds upon over 20 years of expertise in image processing algorithm research and more than 15 years of experience in developing open-source software for image processing and digital art
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to the causal abstraction research direction, which aims to build rigorous benchmark for evaluating AI interpretability using the framework of causal abstraction and develop new interpretability methods
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of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted computations. The postdoctoral researcher will be supervised by Jean-Christophe Mourrat, in