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Field
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for Quantum-enhanced, distributed radar signal processing techniques that maximise target Signal-to-Noise Ratio (SNR). The algorithms we will derive will be applied and tested in the context of target detection
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action discretization, exploration parameters, and decision intervals significantly affects algorithmic convergence and system performance. Distributional RL techniques, such as quantile regression and
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edge AI hardware/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a
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/software. Contribute to designing and evaluating scheduling algorithms for virtualized or distributed AI resources under varying load, latency, and failure conditions. Build and test a scenario generator for
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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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between things, developing the mathematical and computational foundations for optimal information transfer between surfaces and volumetric current distributions in complex scattering media. The research
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of elements) of the model.; 3) develop an optimization algorithm based on genetic algorithms and metamodels and 4) design functionally graded OC scaffolds using different biomaterials. The doctoral candidate
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algorithms * Parallel algorithms and distributed computing * Parameterized complexity and structural graph theory * Random structures and randomized algorithms * Sublinear and streaming algorithms
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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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, and convergence measurements—often fail to detect distributed or deep-seated defects, require manual access, and offer limited spatial and temporal resolution. These methods also lack the sensitivity