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research verbally and in writing. The position also includes teaching on Chalmers' undergraduate level or performing other duties corresponding to 10% of working hours Contract terms: Full-time temporary
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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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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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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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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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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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gradually become a cornerstone of modern life. Its success depends on immense computational effort and extended training times to produce sophisticated models. To handle the scale of these models, distributed
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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