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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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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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(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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graph processing frameworks, graph databases, graph learning frameworks, knowledge graph systems, and graph mining systems. While each of them is specialized on a specific type of task and is highly
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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
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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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13.03.2023, Wissenschaftliches Personal We are looking for motivated students to work on the development and implementation of a cheap and scalable ceramic processing concept towards a fully sprayed
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integration of vehicles into mobility and energy systems. We improve the efficiency, sustainability and economics of electric vehicles by optimizing and accelerating the integration of components up to complex