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-correction. This PhD falls into the fields of error-correction and Deep Learning. Due to the inherent unreliability of the DNA storage support, the goal will be to develop advanced deep learning models
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datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning). The goals are to develop new computational methods that allow the scientific inference
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. The project is led by Heiko Schütt and will employ one PostDoc and one PhD student. About the role... You will develop new Bayesian methods to compare deep neural network and other artificial representations
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methods based on state-space models [3] have demonstrated strong capabilities in modeling very long sequences. In this context, these methods provide the perfect alternative to standard deep learning
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(APC) is part of the Deep Underground Neutrino Experiment (DUNE) which is an international collaboration with more than a thousand members and more than 30 countries involved. The project is hosted by
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on advanced AI methodologies. Incorporating physics-guided deep learning models that explicitly integrate the underlying MRI signal formation process to enhance reconstruction reliability and interpretability
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DeepTypo project, which aims to use deep learning models to study the typography of languages. The work will focus on creating a bidirectional system that (i) from an audio recording will predict
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these techniques to DL in edge-cloud continuum systems. References [1] B. McMahan, et al. 2017. Communication-Efficient Learning of Deep Networks from Decentralized Data. In Proceedings of the 20th International
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computer science (notably from the artificial intelligence and deep-learning field), requiring the collaboration of experts with different expertise. The ambition of the project resides in popularizing AI
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an industrial track (2 years at IMT Atlantique + 12 months at Sony STC, Germany). 1.1. Domain and scientific/technical context Generative and creative systems based on Deep Learning have recently emerged under