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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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. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data
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Statistics section, include: Algorithms , focusing on online and approximation algorithms, graph and parameterized algorithms, string algorithms, data structures, combinatorial optimization, algorithmic
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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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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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, 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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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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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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), including algorithm design, implementation, and experimental validation conduct research on distributed processing schemes for hearing aid algorithms, integrating advanced signal processing methods, low