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03.06.2021, Academic staff The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and privacy-preserved
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03.06.2021, Academic staff The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and privacy-preserved
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? Then this position is just right for you! About us In the Autonomous Vehicle Lab, we develop the vehicle of the future with intelligent algorithms and methods. We are involved in numerous projects in
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on design automation for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. One of the main challenges in this design process is
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) to determine greenhouse gas and pollutant emissions in cities using atmospheric measurements (MUCCnet: https://atmosphere.ei.tum.de/ ) and in-situ sensor networks in ICOS Cities project (https://www.icos-cp.eu
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focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how-to-store
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AI4SmartCities that aims at technology transfer. The AI4SmartCities team is aimed to eventually create a spin-off company. The candidate is intended to conduct market research of AI for Smart Cities algorithms and
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project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures. Your
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be achieved, for example, by developing learning algorithms and bringing together different sensor systems in the vehicle and on the road. Where you put the focus - that is up to you. The concepts
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coding skills to design highly efficient algorithms. Solid knowledge in the areas of algorithmics, optimization problems, as well as experience with SAT/SMT solvers or machine learning is an advantage