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Field
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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(Berlin) in a close partnership with the Forschungszentrum Jülich, contributing to algorithm development, computational tool implementation, and validation with experimental partners (TU Graz and
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the development of methods and models refinements, analyses, and optimizations for scale-grid TES integration and operation planning algorithm. RESTORATIVE consists of 17 PhD students at 7 universities and 4
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Twins & Energy Analytics Forecasting & Optimization Algorithms Green Hydrogen Technologies ICT Applications in Energy Systems GIS Applications in Energy Planning Interdisciplinary and innovative research
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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-of-information metrics. Propose computational algorithms to estimate these metrics. Design and execute simulation studies to evaluate the above. Develop and test statistical software. Write user-friendly guidance
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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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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will focus on developing theoretical and algorithmic foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic