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Field
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POLARIS doctoral network POLARIS is a European Marie Skłodowska-Curie Doctoral Network focused on accelerating therapy development for leukodystrophies: rare genetic disorders affecting the brain's
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-centric micromanufacturing technologies for next-generation healthcare and MedTech applications. The project offers the possibility to pursue the PhD within the network at different universities and
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-centric micromanufacturing technologies for next-generation healthcare and MedTech applications. The project offers the possibility to pursue the PhD within the network at different universities and
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particles and flowing water across different spatial and temporal scales, while keeping the models computationally efficient. The research builds on an Eulerian two-phase modelling approach previously applied
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quantum technology by training researchers who will help build the future of secure and efficient communication networks: the Quantum Internet. PhD project - Important the start date for this PhD is 1 st
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detection and free space estimation. However, current neural networks are typically developed for a specific radar configuration and task, and often generalize poorly to other sensors. At the same time, large
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networks are typically developed for a specific radar configuration and task, and often generalize poorly to other sensors. At the same time, large scale radar datasets with high quality labels remain scarce
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Network ReDiLEEP (https://redileep.eu/ ). ReDiLEEP brings together leading universities, research institutes, and non-academic partners across Europe and beyond to advance response diversity research and
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the Technical University of Munich (TUM), the network brings together ten universities with regulators, public agencies, international organisations and research networks. The doctoral projects investigate how
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predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object