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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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researchers in Science and Technology Studies (STS) exploring the interactions between science, technology and society. As a vibrant hub for STS research in Germany, it offers a highly stimulating and
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pension scheme special annual payment Leibniz-LSB@TUM is committed to equal opportunities, diversity, and respectful interaction. We welcome applications regardless of gender, nationality, ethnic and social
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designed flow cell is coupled to inductively coupled plasma mass spectrometry and the stability against dissolution will be assessed. This will be done with collaboration partners around the
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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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principles and machine learning design patterns. Be highly motivated and a team player with excellent communication and presentation skills, including experience in communicating across discipline boundaries
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skills in Python and PyTorch including fundamental software engineering principles and machine learning design patterns. Be highly motivated and a team player with excellent communication and presentation
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world is continuously sensed and/or explicitly shared to provide a model of 6G network environment and its users – encouraging design of algorithms, protocols, and systems that “intelligently” fuse data
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available in the further tabs (e.g. “Application requirements”). Programme Description Higher education graduates of outstanding academic merit who plan to complete a doctoral programme or carry out