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and communication systems. You will work with real measurement data and participate in both algorithm development and experimental validation. You will collaborate with industrial and academic partners
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communication infrastructure design and evaluation, reliable communication technologies, protocols and algorithms, internet of things and wired/wireless communication at all network layers. The candidate should
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control strategies based on Model Predictive Control (MPC) and real-time sensor feedback to dynamically adjust process parameters and recipes. The research will integrate data-driven models, material
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is to develop machine-learning-based algorithms for transmitter pre-distortion and receiver post-distortion architectures that enable distortion-free quantum communication systems. A key focus will be
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theory, and is expected to have experience with the practical implementation of control algorithms. Who we are Learning and Decision at AAU, founded in 2020, focuses on developing mathematical methods
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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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efficiency through parallelism (time-, frequency-, and mode-multiplexing), with a specific focus on photonic reservoir computing Relate parallelism to applications, e.g., algorithmic parallelism, multi-tasking
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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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specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in the computational biology and
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At the Faculty of Engineering and Science, Department of Materials and Production one or more Postdoc positions in the area of Optimization and Algorithm Design are open for appointment from April