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Lomet, Research Engineer in AI at LIAD, CEA Saclay · Marianne Clausel (University of Lorraine), scientific lead of the national PEPR causali-t-ai program, · Myriam Tami, Associate Professor
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have a PhD in computer science, mathematics, physics, or related fields, with a passion for programming. A desire to contribute to the development of open-source software within the context of the agreed
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, or examples, these aspects are of utmost importance and need to be explored to provide convincing and well-grounded arguments [1]. This PhD program will propose to explore advanced methods to detect implicit
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and neural computation. By leveraging the rich data repository on the larva’s neural connectome and muscular structure, the project seeks to create accurate simulations that can inform biological
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Description This PhD project bridges computational neuroscience and machine learning to study the mechanisms of active forgetting—or unlearning—through the lens of both biological and artificial systems
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understanding of how neural coding and speech perception are degraded in individuals with Auditory Neuropathy Spectrum Disorders (ANSD) [1]. The project leverages physiologically-informed computational models
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, or the misinterpretation of some inputs to result in a particular behaviour that is favourable to the attacker. In this thesis, the PhD candidate will first study the impact of decentralizing ML algorithms
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possibility to go beyond discretization biases is to use of implicit regularization given by neural radiance fields [MST+21] which have been showed to be effective in the continuous representation of scalar
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of the auditory pathway using multi-electrode arrays. Requirements We are looking for individuals who want to study neural coding in the context of hearing and who meet the following criteria: 1) PhD in
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the ability of neural networks to learn unknown posterior distributions distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this PhD thesis is to develop