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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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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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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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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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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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energy resources. The expected outcomes include technical advancement of distributed algorithms for managing energy resources at customer premises. The benefits include more resilient, secure, private, and