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Field
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tasks that best suit your strengths. This could involve the design, optimization, and fabrication of advanced devices using numerical methods like FDTD; taking charge of spectroscopic experiments
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leveraged to improve existing modulation models describing how large scales alter heat transfer. Optimal oscillations will be designed using reinforcement learning. Extending inner-outer interaction models
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research group in computer vision and machine learning, with seminal results in 3D reconstruction from images, scene understanding, deep learning, optimization, sparsity, etc. IMAGINE is part of
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 17 days ago
are available. The user defines a graph of tasks to be executed. This graph is then forwarded to the Dask scheduler. The scheduler is in charge of (1) optimizing the task graph and (2) distributing the tasks
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intestinal duct section. To achieve this, we will address the inverse design problem using physics-informed machine learning that consists of determining the optimal structure and material distribution
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optimization of complex systems, intelligent data and information systems, as well as networks, distributed systems, and security. LIMOS stands out for its interdisciplinary approach, combining theoretical
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) understanding of the mathematical foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks, 3) problem solving
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optimizations are still needed to adapt the translation of these mRNAs to the cell types of interest. As part of a collaboration with Chantal Pichon's team (University of Orleans), this project aims to use
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activities, as well as the development and/or validation of the performance of various hydrogeological and hydrological calculation codes. You will bring innovative approaches to optimize and anticipate
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a