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atom is a promising route to tailor the electronic structure and to realise artificial matter with exotic electron ground states. Another promising route towards physical implementations of energy-based
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states, often next to material phases with charge order. On top of that, creating material atom by atom is a promising route to tailor the electronic structure and to realise artificial matter with exotic
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the electronic structure and to realise artificial matter with exotic electron ground states. Another promising route towards physical implementations of energy-based machine learning and neuromorphic hardware is
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. Thermoplastic composites, combined with novel material architectures, are central to this transition, enabling recyclable, lightweight structures. Research now targets energy-efficient, automated processes and
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of this Research Fellowship is to contribute to a deeper, theory-driven understanding of the global Earth observation (EO) market and industry, identifying its structural dynamics, competitive landscape and long
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“Hydrogen and green electrons for carbon-based chemistry” (HyCarb) of the National Growth Fund program GroenvermogenNL involving knowledge institutions and companies in the Netherlands. Tasks and
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, which causes reduced performance and accelerated material degradation in seawater. This project will experimentally investigate cavitation erosion in composite materials and develop a structural health
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in context, e.g., reacting to a partner’s gesture, resembling an object they refer to in the environment. Exploring how these models can enhance human-computer interaction and improve our understanding
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enhance human-computer interaction and improve our understanding of multimodal communication. To do so, you will have full access to motion-capture and virtual-reality labs, 3D animation tools, and GPU
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, are central to this transition, enabling recyclable, lightweight structures. Research now targets energy-efficient, automated processes and machinery to deliver high-quality components for the next generation