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, combining biomechanical realism, synthetic data generation, and privacy-preserving visualization within a single framework, to enable both clinical assessment and secure, long-term home monitoring. You will
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and validate a novel single-camera markerless motion capture system, combining biomechanical realism, synthetic data generation, and privacy-preserving visualization within a single framework, to enable
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, navigation and control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line
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outputs. Cover Letter outlining your qualifications and vision for this position (max. 1–2 pages). Executive summary of PhD dissertation. Any sample of related work examples (e.g., data visualizations, code
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vision for this position (max. 1–2 pages). Executive summary of PhD dissertation. Any sample of related work examples (e.g., data visualizations, code repositories, data analyses) is appreciated. Please
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, transitions of control, driver awareness, and the communication of system capabilities and limitations. The project brings together expertise from human-computer interaction, AI, human factors, cognitive
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, and construction-task constraints, supporting real-time 3D visualization, human monitoring, algorithm testing, and pre-assembly validation. The platform will serve both as a research environment for