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Digitalising populations of structural systems using machine learning (S3.5-MAC-Dardeno) School of Mechanical, Aerospace and Civil Engineering PhD Research Project Competition Funded Students
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Multi-modal Understanding of Human Heart (S3.5-COM-CChen2) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Chen Chen, Prof Andy Swift Application Deadline
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this information reliably can unlock breakthroughs in areas such as healthcare, physiotherapy, robotics, and human-computer interaction. This PhD project will explore new ways of understanding human motion by
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Award at the University of Sheffield. Imagine being able to check that a powerful quantum computer has performed a calculation correctly without having to repeat the computation or learn the private data
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as the Insigneo Institute theme co-director for Healthcare Data/AI and the N8 Centre of Excellence in Computationally Intensive Research theme lead for Machine Learning. About the School/Research Group
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speech models to predict communication decline and intelligibility changes for longitudinal monitoring; Design machine learning methods to model relationships between vocal characteristics and impact on
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developing a computational model that simulates blood flow for ICH patients. The research will exploit a powerful new approach — physics- informed neural networks (PINNs) — that combines machine learning with
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manufacturing? Benefits Earn While You Learn: Get a fully funded four-year postgraduate research degree (EngD or PhD) with an annual tax-free stipend of £28,000 (that’s equivalent to a £34,000 salary!). We’ve got
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physical systems. You will explore how the dynamic behaviour of nanomagnetic devices can be used to realise these KAN functions directly in hardware. Working with a combination of modelling, machine learning
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to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be developed to efficiently