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models. Your tasks: Research, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in
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technology, and process optimization using mathematic modeling - Evaluate modified growth factors under real conditions with medium recycling - Independent work on research projects - Close cooperation with
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is to enable safe and agile behavior of the autonomous vehicle. You will be responsible for the conception, implementation and evaluation of the new algorithms. In addition to your technical work, you
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vehicle actions in complex multi-vehicle environments. You will be responsible for the conception, implementation and evaluation of the new algorithms. In addition to your technical work, you will take
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of the doctoral project is positively evaluated after the first two years. CMS’s inter-disciplinary team is performing research in the broad field of computational methods for the built environment. Particular
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techniques we evaluate the catalyst’s performance. This enables the examination of numerous materials in a short time and thus accelerates the discovery of new materials. The corresponding reaction mechanisms
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the first semester Continuous supervision by two professors / senior scientists and one mentor Regular evaluation of the students' work/study achievements Active support is given to the students in
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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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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
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include: Literature research Designing, implementing, and evaluating novel machine learning approaches to retrieve buildings in 3D, building settlement types, and distribution of construction sites at very