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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image
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profile: • Very good degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault
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, Management Science, Business Analytics, or a related field. Strong analytical skills with experience in AI, machine learning, or data analytics. Very good English skills in writing and communication
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Engineering or a related discipline. Experiences in Machine Learning, Deep Learning and Artificial Intelligence. Strong programming skills (Python) Good knowledge of AI frameworks like TensorFlow, PyTorch
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for our clients from numerous industries. Overarching top topics at Fraunhofer ITWM are Machine Learning as well as Artificial Intelligence and Renewable Energies or Sustainability. In addition, Next
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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The Max Planck ETH Center for Learning Systems (CLS) addresses cross-disciplinary research questions in the design and analysis of natural and man-made learning systems. The excellent engineering
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to obtain a doctoral degree in aeronautics at the Technical University of Munich or the University of the German Armed Forces Munich. Academic Requirements degree in a subject related to aerospace technology
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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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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