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contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 2 months 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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the project's personalized treatment algorithms. For further information, please contact Prof. Dr. Antonio del Sol, antonio.delsol [at] uni.lu . Your profile Ph.D. degree in computational biology, bioinformatics
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above Strong mathematical and algorithmic background A pro-active approach to achieving research excellence Commitment, team working and a critical mind Fluent written and verbal communication skills in
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"Phase-space-inspired numerical methods for high-frequency wave scattering: from semiclassical analysis through numerical analysis to implementation". The design of fast and reliable algorithms
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 3 months ago
that diffusion models are a fundamental divergence from traditional deep learning paradigms. This suggests that existing generalisation theories are insufficient and highlights the need for a bespoke, algorithm
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed
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theoretical foundations of modern learning algorithms. The position will be supervised by Florence d’Alché-Buc, Charlotte Laclau, and with Rémi Flamary and Karim Lounici from École Polytechnique
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signal-to noise Post-processing: denoising, reconstruction algorithms Comparison with high-field MRI: deep-learning and other AI modalities for low-field MRI optimization Close cooperation with
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algorithms. The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters