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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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and their processing on the FPGA of a frame grabber card You will program the PC software for configuring and controlling the algorithms on the FPGA Your tasks will include designing the transfer
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operating conditions Design and implement optimization algorithms to improve the performance of the engine, battery, fuel cell, transmission, and hydraulic systems, considering constraints such as component
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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 on semiconductor
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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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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available in the further tabs (e.g. “Application requirements”). Programme Description The research and training programme focusses on the mathematical and algorithmic foundations of reliable AI along with
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Computational Molecular Medicine, led by Prof Julien Gagneur, develops computational approaches to study the genetic basis of gene regulation and its implication in diseases. Applications of our work range from
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21.12.2021, Wissenschaftliches Personal The Department of Computer Science, Technical University of Munich, has a vacancy for a PhD candidate/researcher position in the area of efficient algorithms
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31.07.2023, Wissenschaftliches Personal Within the Joint Academy for Doctoral Studies (JADS) program of Technical University of Munich and Imperial College London, the Professorship of Energy