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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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14.12.2022, Academic staff The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics, and high
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05.04.2023, Academic staff We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated learning
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05.04.2023, Academic staff We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated learning
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Learning algorithms for EDA in terms of Computational Complexity, Performance Scores, etc. To learn more about our previous work, please check out our website ( www.cda.cit.tum.de/research/machine_learning
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technologies and develop algorithms and software tools dedicated to accelerating research on multiple levels. We are working at the intersection of computer science, physics, and material science to push the
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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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manipulation detection. Another focus is the development of algorithms for the areas of virtual product development, intelligent actuator-sensor systems and audio for the automotive sector. There are currently
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic