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! This unique research opportunity revolves around the physics of distributed robotic systems, mechanical metamaterials, active matter, and embodied intelligence, combining table-top experiments and
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have unpublished results showing that linear combinations and operations on the ansatz can also be included. This will allow us to perform the ground state search and the dynamics without resorting
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SINTEF. The project aims to develop an automated high-throughput platform for physiologically relevant cell research by combining robotics, microfluidics, advanced sensors, cloud-connected software, and
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with neurological disorders, yet its effects on everyday movement remain poorly understood. In this PhD project, you will combine cutting-edge physiological measurements, motion analysis and wearable
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microbiome, and their specialized metabolites. To address this question, the project will develop an integrative approach combining chemical ecology, microbiome analysis, multimodal metabolomics, and
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sensors capable of characterizing the dynamic state of buildings and their inhabitants. By combining multi-microphone acquisition techniques with state-of-the-art machine learning methods, acoustic sensing
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of Josephson junctions. The methodology combines TEM, geometric phase analysis (GPA), chemical analysis (EDX), and growth modeling. Experiments using 4D-STEM coupled with electron ptychography will provide
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transition. See: https://www.tudelft.nl/en/2026/tbm/tpm-researchers-receive-nwo-kic-consumer-behaviour-for-a-circular-system-transition-grant . The project includes 2 PhD positions, 2 Postdoc positions, and
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combine academic excellence with relevance for practice — including through innovative formats of dissemination and co-creation with industry. Proposals must address the project’s prospective interactions
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environments, and distributional shifts. The research will combine probabilistic modelling, network-based representations, and modern AI methods to enable scalable and interpretable decision-making in complex