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each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In FlexMobility we propose a holistic approach to design
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, and each core, and eventually each mode, must benefit from controlled gain, so as not to create a gain difference between cores, and to guarantee the balance of the system as a whole. While rare earths
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additional mechanical losses. Unlike conventional static devices, the vortex generators studied here adapt their shape and/or position naturally in response to flow conditions. This self-adaptative behavior
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the focus areas are stochastic optimization and equilibrium modelling in energy systems and markets. Position 1: PhD Project - “Optimisation of household demand response” The project aims to achieve
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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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called SiCPIC. The project consists of 15 PhD students at 5 universities and one company. The project has partners from five different EU countries. All, 15 PhD projects are within the overall theme
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Network project called SiCPIC. The project consists of 15 PhD students at 5 universities and one company. The project has partners from five different EU countries. All, 15 PhD projects are within
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these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine
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environmental footprint.In this context, the optimization of material recovery from end-of-life vehicle scrap is challenged not only by the heterogeneous and evolving nature of this scrap, but also by the diverse
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts