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Do you have a background in deep learning and computer vision? Are you independent, creative and eager to take initiatives? Do you enjoy working in an international research group and interacting
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of interior spaces; and to develop a computer vision and deep/reinforcement learning approaches to combine and integrate imagery from the UAV, but also satellite imagery or data from other environmental sensors
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develop a computer vision and deep/reinforcement learning approaches to combine and integrate imagery from the UAV, but also satellite imagery or data from other environmental sensors. Besides this, you
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transparent and intelligible. Although explainable AI methods can shed some light on the inner workings of black-box machine learning models such as deep neural networks, they have severe drawbacks and
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of black-box machine learning models such as deep neural networks, they have severe drawbacks and limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable
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workings of black-box machine learning models such as deep neural networks, they have severe drawbacks and limitations. The field of interpretable machine learning aims to fill this gap by developing
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this project, you will combine a deep knowledge of physical chemistry with robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning
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Vacancies PhD Candidate Infrastructure monitoring and NaTech disaster response with drones and machine learning Key takeaways The project is part of a large-scale research project funded through
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reducing demand. However, demand drivers are manifold, including technology advancements, population and economic trends, and their future developments come with deep uncertainties. Infrastructure policies
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an interdisciplinary very active consortium called EVOLF. Job requirements Qualified candidates have a Master in physics, chemistry, engineering, or a related field. Successful candidates are motivated by a deep