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Field
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networks by analyzing their dynamical systems and probabilistic asymptotic behavior, improving and generalizing diffusion-based generative AI using insights from numerical and stochastic analysis, and making
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predictions to conventional continuum predictions to understand the relationships between the different theoretical frameworks. The analysis will be accompanied by detailed numerical computations in
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on numerical aspects of the network model analysis. Being part of the wider Mathematical Neuroscience research theme within the School of Mathematical Sciences which currently includes 7 members of academic
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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
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flow regime ranging from steady laminar to unsteady turbulent configurations, there is also potential to extend the analysis to compressible flows and structural analysis. This research is highly
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fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications
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utilise numerical techniques including the finite element method to describe biofluid flow and deformation in the human brain tissue. Parameters are inferred from clinical data including medical images
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Supervisory Team: Prof Neil Sandham PhD Supervisor: Neil Sandham Project description: This project is focused on scale-resolving simulations (large-eddy and direct numerical simulation) combined
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to enhance the UK’s energy system resilience through a whole-system analysis approach. Building on the proven WeSIM model, RENEW will upgrade its capabilities to incorporate electrified district heating and
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scientific discipline. • First-rate analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices/mechatronics •Ability to develop kinematic and