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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 methods
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Your Job: The focus of this Master Thesis is the development of an optimization to minimize energy consumption in an existing model of non-road mobile machinery (NRMM). Optimization opportunities
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energy footprint. What you will do Research various algorithms suitable for energy aware scheduling Develop a custom algorithm for energy awareness scheduling Perform experiments and evaluate performance
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into the setting of metabolic flux inference and, with inspiration from existing algorithms, develop tailored MCMC algorithms. You will implement the ensuing algorithms in an existing C++ framework, validate and
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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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The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems - so-called intelligent systems for various applications. The systems
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The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems for various applications. The systems combine electronic components
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processing workflows including QC and reproducibility metrics * APIs and packages supporting the development of new algorithms spanning large * language modeling of DNA and RNA sequences, and algorithms
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to the road? Then this position is just right for you! About us In the Autonomous Vehicle Lab, we develop the vehicle of the future with intelligent algorithms and methods. We are involved in numerous projects
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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