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Field
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: Strong mathematical ability. Experience of scientific programming and algorithm development. Knowledge in wireless communication systems and the theory behind. Knowledge in distributed optimization
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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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) development, validation and application testing of a novel distributed fiber-optic acoustic measurement system (DAS) for structural health monitoring (SHM) of underground gas cavern storage facilities and
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, data-limited, and dynamically evolving environments. Applications include complex engineered systems such as intelligent communication networks, distributed computing platforms, and quantum-enhanced
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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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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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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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), including algorithm design, implementation, and experimental validation conduct research on distributed processing schemes for hearing aid algorithms, integrating advanced signal processing methods, low
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
resources. To fill this gap, this proposal aims to design novel distributed and lightweight LLMs for spectrum management in aerial 6G networks. Specifically, the project will design wireless-aware data
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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