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Job Description DTU Electro invites applications for a PhD position in digital signal processing and machine-learning-enabled continuous-variable quantum key distribution (CV-QKD). The position is
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federated knowledge graph framework that facilitates the querying, consolidation, analysis, and interpretation of distributed proteomics-focused clinical knowledge graphs. To achieve this, we will employ
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describing the effect of conditions on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm
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will be an asset. The PhD will be supervised by Professor Helene Friis Ratner and conducted as part of the Algorithms, Data and Democracy project, founded by the VELUX Foundations. For more information
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optimal control, robust control, distributed control, and model predictive control. A background in power system analysis, dynamics, control and/or converter control is considered a strong advantage
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Relate parallelism to applications, e.g., algorithmic parallelism, multi-tasking, etc. Address nonlinear equalization in optical signal transmission and provide a comparison with neuromorphic electronics
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine
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will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be used. This part of the three
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contribute to the development of novel algorithms and methodologies that enhance the robustness and accuracy of acoustic measurements. We are looking for a highly motivated candidate, with a relevant MSc
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hardware modification. The AI will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be