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Theoretical models for gravitational wave signals emitted by coalescing compact binaries are the cornerstone of modern gravitational wave astrophysics. Among the most pressing challenges
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. Previous experience in computational modelling, air quality or psychology is desirable. The Research Project The overall aim of this PhD project is to understand how indoor air quality (IAQ) affects
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our ability to predictably control and exploit the drop for useful tasks. The proposed project has two aims: First, to develop computational models to quantitatively predict the response of chemically
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Cardiometabolic diseases (CVMD), such as heart disease and type 2 diabetes, represent a major global health burden and exhibit stark ethnic disparities. Current clinical prediction models, even
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the corrosion of reinforcing steel, which compromises safety, durability, and sustainability. Current corrosion prediction models often fall short because they rely on oversimplified assumptions and
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collaboration with modelling or industrial partners Candidate Requirements We welcome applications from candidates with the following background: Academic degree (BSc / MSc or equivalent) in Materials Science
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interactions with potential pathogens. To achieve this objective, we will use the genetically tractable model fungus Zymoseptoria tritici. This fungus also causes Septoria tritici blotch (STB) disease of wheat
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aims to determine the link between lipid remodelling, antimicrobial resistance and intracellular survival using B. cenocepacia as the model organism. The project is supervised by Professor Yin Chen
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wireless communication systems. The PhD student will carry out specifically the following initial tasks: implementation, and calibration of the microscopy system; electromagnetic modelling of the near-field
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the necessary theoretical tools, using cavity quantum electrodynamic (QED) descriptions, to model and understand this complex interaction between plasmons and molecules, to reveal the necessary procedures