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Field
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use dynamic simulations to carry out system studies that depict the future grid. To meet the resulting challenges, we develop new control algorithms and analyse their effect. These include, for example
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algorithms to analyze OMICS data (e.g., genome, transcriptome, proteome, microbiome) from patient samples and basic research perform single-cell RNA-Seq and spatial transcriptomics analysis apply artificial
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Media (EDM), the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms, Implementations (RTG π³), the UBRA AI Center for Health Care , and the ZeMKI
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efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further
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algorithms. This is a hands-on opportunity to apply state-of-the-art methods to patient samples within the largest and most advanced scientific organization in Germany. Learn more about us and our work here
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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but
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of AR glasses that support local AI models Integration of additional sensor technology to enable stroke detection Development of algorithms and application of AI models to recognize stroke symptoms
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creating reference test cases for comparative evaluation of new methods and algorithms. We are seeking a Research Associate specializing in Machine Learning to contribute to the digital analysis and
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: • Mathematical derivation, analysis, and comparison of models, methods, and simulation approaches. • Rapid prototyping of new ideas in custom code. • Implementation of new models, methods, and algorithms
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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and