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Field
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Number of Opportunities Available 1 fully funded place Department Centre for Doctoral Training in the Modelling of Heterogeneous Materials (HetSys), Department of Physics About the project: Advanced
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About the ProjectProject details: Next-generation networks are rapidly outscaling the capabilities of traditional management paradigms. While early AI/ML models offered a degree of automation, they
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Number of Opportunities Available 1 fully funded place Department Centre for Doctoral Training in the Modelling of Heterogeneous Materials (HetSys), Department of Physics About the project: Bottom
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contribute to pioneering computational tools that extend far beyond potassium. About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact HetSys (Centre for Doctoral Training in Modelling
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early as the advert may be removed before the deadline. High-dimensional computations are ubiquitous in science and engineering, often arising from models with numerous parameters. For instance
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motivated PhD candidate with interests and skills in computational modelling and simulations, fluid dynamics, mechanical engineering, physics and applied mathematics. You should have experience in one or more
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of pseudorange correction models. Enforcing such constraints offers substantial potential benefits, including faster convergence, improved generalisation, and reduced overfitting. At the same time, these benefits
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, memory, and energy requirements. The successful candidate will explore novel algorithms and model-design strategies that allow AI systems to operate effectively on edge devices, clinical environments
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pilots to real-world systems. The overarching aim is to deliver a scalable approach, pairing shared “aggregator” models with household-specific “client” models that exchange knowledge while keeping data
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systems, providing early detection of adverse events such as infection and inflammation. The project will involve sensor design and modelling, prototype development, electrochemical characterisation, and