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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from
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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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-edge academic insight with real-world robotics applications. The PhD project will focus on the design of advanced control and decision-making algorithms to enhance the intelligence, autonomy, and
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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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pooling coordination schemes for CF-based 6G RANs. His/Her work will adress objectives like: (i) develop low-complexity ML algorithms for efficient multi-objective network optimization, radio resources
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process. By integrating simulation-informed priors into the reconstruction algorithm, we aim to significantly improve both accuracy and sensitivity. The position is hosted at the Fritz-Haber-Institut
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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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with sufficient accuracy using fast parametric algorithms and machine learning (ML) models instead of time-consuming simulations to evaluate scenarios for improving the user experience along cycling and
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artificial intelligence and control systems. In this project, you will design new algorithms for semantic communication between the cloud and autonomous systems—technology that can transform how robots, drones
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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