51 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at Technical University of Munich in Germany
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in September 2025 or shortly after, for a term of 4 years. The postdoc will join the ERC-Starting Grant project team on “Participatory Algorithmic Justice: A multi-sited ethnography to advance
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Do a PostDoc in Pathology AI! 11.10.2023, Wissenschaftliches Personal The Computational Pathology Lab at the Technical University of Munich (TUM), TUM School of Computation, Information and
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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• Integrated sensing and communication: fundamental limits and algorithm design (1 PhD, Mari Kobayashi, mari.kobayashi@tum.de) • Optical fiber channel modeling, receiver processing, and coding (1PhD, Gerhard
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(with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in
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' prognosis or treatment decisions. For modeling, we use both public and proprietary clinical and research data greatly enriched by our own repository of digital pathology images. A further focus lies on
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zusammen mit insgesamt elf Postdoc WissenschaftlerInnen aktiv am wissenschaftlich-akademischen Diskurs zur aktuellen Forschungs- und Entwicklungsfragen im Bereich des Grünen Wasserstoffs teilnehmen. Von
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mobility systems through practical and laboratory tests as well as sophisticated simulations. We not only publish research results gained at numerous conferences and in journals, but also make our software
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning