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Field
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, PhD Sharon Rossiter, PhD Application process To apply for the studentship please complete the application form via the above 'Apply' button and email it with a copy of your CV, two academic references
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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be testing and optimising predictive models for use in realistic healthcare settings. This studentship will suit a student interested in working in health data science, particularly with an interest in
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excellent understanding in power system dynamics, power electronics and control. Experience in working with power systems dynamic simulation will be helpful, but not necessary to apply for the position. How
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. Our preliminary work has shown that such an adapter can enable a consistent dose to be extruded and spread onto simulated paediatric lesions, where one FTU now covers an area of just two fingers. We
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around three core scientific pillars—regenerative medicine, biomaterial science, and translational research models—SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and
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remain largely unexplored. This research will be carried out by using the world-leading research facilities (high temperature experiment, advanced characterisation and modelling) at the Advanced Steel
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of interest, and two academic references (submitted by the deadline). The application portal will also ask for a research proposal, however, since the project is already defined, you may copy the project
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new