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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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The overall aim of this PhD project is to understand how indoor air quality (IAQ) affects the health of children and adolescents, including their mental health with the aim of creating healthier
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spectrum of neurological symptoms. This PhD project will explore how mTOR dysregulation drives glial activation, complement-mediated CNS injury and neural circuit dysfunction. Using organotypic brain slice
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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Qualification Type: PhD Location: Nottingham Funding For: UK Students Funding amount: Full tuition fee waiver pa (Home Students only) and stipend at above UKRI rates pa (currently at £20,780
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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failure before components are built? We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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The project: We invite applications for a fully funded PhD studentship in the Solid Mechanics Group at the University of Bristol to work on the predictive modeling of hydrogen-induced damage in