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models were successfully developed with methods of Quantum Machine Learning. In cooperation with the University partners the aim of this project ls to translate classical analysis and simulation algorithms
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and classification of cellular populations and niches, and the development of both classical and AI/ML-based computational approaches to condense and interpret the full breadth of genetic and molecular
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: New Perspectives for Science". Details of the research activities as well as publications and background information are available on the group website: https://www.soft-matter.uni-tuebingen.de
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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 network coding
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for air quality monitoring are urgently needed to preserve air quality, human health, and the environment. Current state-of-art commercial miniaturized gas sensors based on classical oxygen conductors