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Field
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fair energy supply system based on renewable energies. We contribute to this with our research priorities of energy supply, energy distribution, energy storage and energy use. Through outstanding
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algorithms into an existing framework, with a focus on efficiency, as well as creation and execution of relevant simulation pipelines: from real data to mathematical and clinically actionable results
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holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
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focus on a current research area in algebra and meaningfully complement the existing research, for example, in the fields of representation theory, algorithmic algebra, tropical geometry, or algebraic
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data infrastructure landscape (including initiatives such as the National Research Data Infrastructure (NFDI), Open Collection, Information and Research Infrastructure (OSIRIS), Distributed System
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, but also in traffic monitoring or in the media context, for example when it comes to automatic metadata extraction and audio manipulation detection. Another focus is the development of algorithms
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, and socially just energy supply system based on renewable energies. We contribute to this with our research focuses on energy provision, energy distribution, energy storage, and energy utilization
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software frameworks Development of new signal processing algorithms (PHY/MAC) in conjunction with software-defined radio hardware Development and validation of AI/ML methods for mobile communications systems
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of multi-omics data sets generated with innovative high-throughput technologies used in Research Sections I and II (e.g. sensory, metabolome, proteome, and transcriptome data) by using efficient algorithms
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and simulation aspects across a wide range of fields - from biomechanics and geophysics to polymer-fluid coupling. Further areas of interest include numerical algorithms for high-dimensional problems