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Autonomous Challenge or EDGAR . Thereby, we research current problem fields in the areas of perception, planning, control, safety and evaluation. Our goal is always to develop the optimal overall software
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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technology, and process optimization using mathematic modeling - Evaluate modified growth factors under real conditions with medium recycling - Independent work on research projects - Close cooperation with
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TEA of a defined process for cultivated meat with material cycling - Optimize the process, also applying mathematic modeling, to improve yield and sustainability - Independent work on research projects
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of the research group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins. Thereby, relevant mechanisms are identified, which allow optimizing
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efficient for it, maintaining and integrating a zoo of graph data systems is a huge challenge and leaves a lot of room for optimizations. Our vision is to explore opportunities to unify core parts of
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network adaptation is crucial for optimal perfusion. In self-organizing life forms, network morphology constantly adapts in response to environmental stimuli towards more homogeneous distribu-tion of flow
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technology constraints Placement & Routing for technology-independent layout generation Clocking and data synchronization Layout validation and verification Technology mapping and optimization To learn more
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since