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Field
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environment using machine learning technologies. This PhD position is part of our research on exploiting social media data for earth observation tasks. The work will be on the topic of developing geographically
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research and travel budget available to best support your research. You will partic-ipate in teaching and supervising students, interact with and learn from the other team members, and re-ceive close
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machine learning technologies. This PhD position is part of the project “Artificial Intelligence for the automated creation of multi-scale digital twins of the built world”, which is funded via the Georg
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learning of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking for highly motivated and
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learning of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking highly motivated and
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learning across space and different cultures. The doctoral students will be encouraged to actively participate in the design of the graduate school programme and thereby shape parts of it according
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challenging PhD programs, which will supplement your research training with outstanding opportunities for career development, continued education and life-long learning. Situated on the foothills of the Alps
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evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric modelling is greatly beneficial. Excellent English and the willingness to learn the German language
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an amount of 1,575 EUR per month. For expenses directly related to the doctoral project (e.g. learning materials, travel), an additional subsidy may be granted on submission of receipts. Application Papers
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group, a multinational insurance company. Tasks Your duties will include: Literature research Designing, implementing, and evaluating novel machine learning approaches to detect building attributes from