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leader in the digital world. We are looking for an Assistant/Associate Professor in Video Processing and Animationwith Deep Learning to jointhe Multimedia (MM)teamin the Image, Data, Signal (IDS
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Health Prevention: Investigate how LLMs associated with deep learning can be used to identify early signs of mental health disorders by analyzing digital diaries, questionnaires, voices features, physical
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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, and deep learning, our goal is to identify new antibiotics and their modes of action. To make these methods accessible to the scientific community, we are developing an open-source platform that will
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l'institut du thorax, INSERM, CNRS, Nantes Université | Nantes, Pays de la Loire | France | 3 months ago
using deep learning approaches. Effectively, in order to prevent cerebrovascular accidents, it is important to study the blood flow at the major bifurcations along the cerebral vascular tree (we mostly
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are looking for a postdoctoral researcher in the field of image generation algorithms (specializing in Deep Learning) for a 12-month position. The work will take place within the IMAGE research team
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without knowledge of the deciphering key, offering significant potential for privacy-preserving deep learning. However, conventional neural networks are not well-suited to the computational constraints
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. Recent advances in Deep Learning [LeCun2005] make it possible to study approaches based on neural networks to solve complex problems. These networks are resource intensive, often making them difficult
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 25 days ago
learning in humanoid robotics for industrial applications. In this project, our goal is to recruit one to two engineers to contribute to: the development of deep learning-based vision tools adapted
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significant computational component. We strongly recommend a background in machine learning and coding. Applicants with a background in areas such as computational neuroscience, reinforcement learning, or deep