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network. This project aims to develop skills for an autonomous mobile robot to perform complex manipulation tasks. Our goal is to enable continuous learning, allowing the robot to improve over time by
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intelligent systems that can learn to interpret complex visual and scientific data, enabling breakthroughs in areas such as autonomous navigation, medical imaging, and materials science. The research group is
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop
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What if you could design systems that not only follow instructions — but understand intent and guarantee correct behavior over time? We are looking for up to two PhD students who want to explore
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our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the mechanisms, and time scales involved at particle scale, for the formation and failure
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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failures. We offer access to unique experimental data and computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel
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individual interested in pursuing a PhD focused on exploring the complex relationship between housing renovation, efforts to reduce climate impact through increased repair and reuse, and the development
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Join us for an exciting and excellent PhD journey to create the future of maintenance! Explore the fascinating future of Net Zero industries where complex and highly automated equipment need