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Learning Algorithm for Grid Optimization linked to Bayesian uncertainty outputs Test bidirectional interaction: Bayesian updates → Reinforcement Learning policy adaptation → grid performance feedback
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-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 and
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you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
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concise code Diligence in implementing, testing and documenting algorithms and results Curiosity about a deeper understanding of Deep Learning architectures What you can expect Fascinating challenges in a
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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promising alternative to classic methods of process optimization due to its adaptive decision making and data efficiency. In this thesis, a BO algorithm for the optimization of laser processes is to be
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environment. We are creative, we shape technology, we design products, we improve processes, we open up new paths. Our clients value our modelling competence, algorithms and software products. We
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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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, 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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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