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Field
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research, including the development or integration of algorithms, decision support tools, predictive models, artificial intelligence, visualization and analysis of health data, as well as the use
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regulation, RNA biology, protein biochemistry, stem cells, bioinformatics, sequence analysis, mathematics, statistics, molecular evolution, or biophysics, and wish to work at the Max Planck Institute
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intelligence. In these research areas we focus on 1) foundations, 2) system design, and 3) applications. IDLab collaborates with many universities and research centres worldwide and jointly develops advanced
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Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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modern technologies is a highly active topic at the interface of fundamental research and applications. The development of quantum technologies has been identified as a national strategic area. Furthermore
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focused on algorithm design and software development, especially in its early stages, we also intend to employ the methods developed for such applications as electrolyte decomposition in metal-ion batteries
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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network aims to deliver fiber-optic quality experiences over wireless links by building the theoretical, algorithmic, and architectural foundations of THz systems. It introduces ultra-MIMO (multiple-input