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Field
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
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. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data. The PhD position will focus on development a comprehensive and AI-driven platform
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of federated algorithms that enable fair management of the advantages and duties of energy communities in which vulnerable people live. The automatic generation of data models using AI technology will enable
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Researcher will influence the direction of application areas and algorithm development, receiving direct training in InSAR processing, geospatial data science, and agricultural remote sensing. Co-supervision
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for photocatalytic degradation and H2 production.Designing multi-objective optimization algorithms to maximize environmental and economic performance. Your RoleAs a PhD researcher, you will: Build and validate hybrid
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Museums and Inclusive Heritage Preservation Platform Labour, Creator Economies, and Algorithmic Change AI in the Creative Industries (cross-faculty potential) Independent Cinema Exhibition and UK Screen
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fundamentals of networking. Objectives: To achieve on-device spectrum sensing using on-board sensors of mobile BSs, empowered by embedded deep learning algorithms; to propose an analytical model for the cell
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to demonstrate real-world feasibility. The overarching goal is to bridge high-level algorithmic innovation with energy-aware hardware deployment, enabling intelligent sensor systems that act as autonomous micro
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both