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focuses on modeling IoT-Fog environments, designing multi-objective optimization algorithms (latency, energy, reliability), and developing strategies for critical IoT applications like smart cities and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
to bandit algorithms when the performance criterion is not the expected outcome but some risk averse measure such as CVaR or entropic risk. The objective is to propose and analyze new risk-aware bandit
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the standardization of acquisitions, Developing deep learning algorithms to define and learn relevant spectral signatures and link them to clinical phenotypes, Evaluating and validating the platform on representative
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algorithms for asthma. The methods to be employed will include cell culture, transcriptomics, proteomics, multiplex assays, flow cytometry, and machine learning. This project combines expertise in cell biology
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models for maritime, aerial, and underwater robots. - Designing, implementing, and evaluating navigation, control, and mission planning algorithms. - Studying multi-robot coordination and human-robot
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consistent thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in
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thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in terms of gradient
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integrating artificial intelligence, from algorithm design to on-sky demonstration. The objective is to design intelligent adaptive optics systems capable of correcting sensor nonlinearities, anticipating
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integration of a non-intrusive power consumption monitoring (NILM) technology into an existing industrial optimization system. More specifically, the missions consist of: Participate in algorithmic and
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that integrate physical constraints (Physics-Informed Neural Networks), as well as for the implementation and optimization of the associated algorithms. The researcher will analyze and interpret experimental and