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Field
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for Artificial Intelligence. The position aims to strengthen methodological and algorithmic work on one or more of the following axes: Optimization and learning on very large models and datasets, improving
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distributions, characterize power under alternatives, and analyze automatic adaptation to intrinsic data structure. The algorithms developed will target scalability to large datasets via adaptivity without manual
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Control for System Engineering department includes the development of methods and tools for optimizing and controlling the dynamic behavior of systems in a wide range of application domains, in
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of promising nanoagents. The objective of this doctoral project is to develop an innovative method for sensing and quantifying the hotspot effect in aqueous suspensions of optically absorbing nanoagents, without
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to support major transitions, train responsible engineers, and place scientific and technical excellence at the service of education, research, and innovation. As part of the France 2030 Superviz project
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are: i) to develop a new selected CI algorithm allowing reaching chemically-accurate results for large compounds; ii) to extend the currently-available database to properties relevant for both core
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
science as part of the ERC Starting Grant project Incorwave, which aims to develop advanced numerical and mathematical methods for passive seismic imaging. The research will focus on two key-directions: (1
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laboratory from Université Côte d’Azur (UCA). He leads the eBRAIN research group and develops an interdisciplinary research activity on embedded bio-inspired artificial intelligence and neuromorphic
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sequences. Development the analysis method and algorithm. 12 to 24 months: Photothermal, photoacoustic and hotspot characterization of several nanoagents with a significantly different hotspot effect
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of the algorithm for real-time planning in the event of unforeseen hazards or new demands. -Calibration and validation of the developed optimization-simulation coupling model with a fleet of robots ***FINANCIAL