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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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advanced mathematical algorithms and AI frameworks for modeling and optimizing power electronic components and systems. To support our team, we are looking for a working student (all genders) in the field
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performance should improve over time as more data becomes available. The diagnostic conclusions will be presented to an operator using a combination of AI-based fault isolation algorithms and data-driven
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Ecole Polytechnique and CNRS, hosted by the Center for Applied Mathematics (CMAP) of Ecole Polytechnique. The Platon project-team focuses on developing innovative methods and algorithms for uncertainty
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and optimize advanced signal processing algorithms for joint communication and sensing. Analyze experimental datasets, extract statistical models, and compare findings across environments, hardware, and
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to make a difference. If this sounds like you, you’ve come to the right place! Responsibilities: Conduct original research on joint communications and radar sensing for spaceborne systems, with a focus on
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traits and remote sensing: 1. Developing innovative new methods --- including both data-driven and physics-based approaches --- for estimating traits from different kinds of remote sensing data (especially
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-critial vibrations from sensor data, enabling data-driven optimization of machining processes. You will also implemet ML algorithms for additional use cases, acceleration workflows and enhancing
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operational practices • Systematically exploring different formulations of mixed-integer constraints in grid optimisation problems • Developing machine learning models to accelerate mixed-integer