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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control
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efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further
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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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rerum naturalium, abbreviated to Dr rer nat) or the academic title PhD. The Department of Mathematics and Computer Science confers the academic degree of Dr rer nat. Alternatively, women can be awarded