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neural networks, covering representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform
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of robust and reliable cell lines. As a core member of our team, you will contribute to the development, optimization, and characterization of cell lines from marine and aquatic species, working toward
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(TU Delft, UTwente), 6 hospitals, 13 companies (including Model Health and Moveshelf), 1 rehabilitation centre, and 5 patient organisations. The Challenge Reliable, long-term monitoring of motor
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patient organisations. The Challenge Reliable, long-term monitoring of motor impairments outside the clinic is essential to support home-based rehabilitation, yet existing markerless motion capture systems
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learning for the analysis of population-scale networks. The position focuses on two pillars of trustworthiness: explainability and privacy-preserving learning. This research direction connects closely
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remain to be addressed before this technology is viable at a commercial scale. One such obstacle is the development and characterization of robust and reliable cell lines. As a core member of our team, you