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. Côte d’Azur & INRIA), will be focused on the development and the understanding of deep latent variables models for unsupervised learning with massive heterogenous data. Although deep learning methods and
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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] and taphonomy of animal bones [Cifuentes-Alcobendas and Dom´ınguez-Rodrigo, 2019] are gradually intensifying. Thus, the present PhD project is an opportunity for the development of original ML solutions
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Simulation and Physics of Drosophila Larva Body Dynamics Introduction The “STRETCHED” project aims to develop a robust, physics-based 3D simulation platform to replicate the motor control dynamics
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the use of synthetic data in precision medicine research and applications through development of AI algorithms, tools and other processes to allow for the enrichment of clinical data sets Providing training
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on scientific projects submitted by research teams of our institute. Train scientific staff from Institut Pasteur Paris and the international network of Institut Pasteur. Develop tools and applications to be
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aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimising PIC algorithms for modern
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procedure. In this context, the proposed PhD project aims to develop an innovative strategy to evaluate the efficiency and quality of surgical care. This strategy is based on data science, combining