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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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environment Geotechnics research at the Department of Architecture and Civil Engineering focuses on the characterisation and modelling of complex geomaterials, particularly natural clays. Our work bridges
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. Research environment Geotechnics research at the Department of Architecture and Civil Engineering focuses on the characterisation and modelling of complex geomaterials, particularly natural clays. Our work
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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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for reactive synthesis. This allows us to describe dynamic behaviors in complex environments over time. You will work with formal tools such as: Planning domains and temporal logic — to describe the required
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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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AI training has emerged as the standard approach, which utilizes thousands of high-performance devices within a data center to collaboratively process tasks. When they are even more complex, the
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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