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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 methods, machine learning
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: 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 and satellite-based
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or friendships between users in a social network. Due to the large variety in data science tasks performed with graph-structured data, different specialized systems have been developed, such as graph processing
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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 the working language is
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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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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
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 control
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13.03.2023, Academic staff 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 Li-based
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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 mobility systems through
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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 Kramer