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tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement learning strategies for comb generation
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focus on the following areas: Subspace tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement
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objective of this PhD position is to advance research in statistical signal processing and machine learning for microphone array data, with a focus on sensing under uncertainty. The successful candidate will
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validated in half-cells and full working batteries at industrial partners at TRL 6. Our objectives: Multiscale modelling to better understand RFB behavior and identify optimal hierarchical shaped pore- and
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align with the objectives of the CopeNLU research group and more specifically with the research interests of the main project supervisor . The overall focus of the PhD will be on trustworthy NLP models
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development. The PhD position will focus on the topic of “Left-behind places and entrepreneurial mobilization”. The objective of the PhD project is to contribute to the question of how structural changes
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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and training with a focus on rural entrepreneurship and development. The PhD position will focus on the topic of “Left-behind places and entrepreneurial mobilization”. The objective of the PhD project
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. The objective of the PhD study is to investigate and address key research and design challenges, including but not limited to: Efficient communication models within timing constraints in quantum applications
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entrepreneurs. The project comprises three major objectives: (1) Identify and explain the emergence of locally integrated models of sustainable energy investments in rural areas in Denmark; (2) Identify and