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Interplay between Algorithms and Combinatorics
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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components and control algorithms for the printing process that take into account our theoretical understanding of the processes occurring and utilizing high-speed in situ data acquisition to respond
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to pursue difficult tasks (under supervision) How to Apply To apply for a PhD studentship, applications must be made directly to the University of Sheffield using the Postgraduate Online Application Form
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at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will involve designing innovative QML approaches and collaborating
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-identified scans, records and sensor feeds to answer questions such as: Can we predict a patient’s response to treatment without ever seeing their raw file? Can an algorithm learn the warning signs of trouble
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for application to fusion reactors, considering factors such as muon flux, detector sensitivity, and data analysis algorithms. PhD candidates will be tasked with developing simulations of complete detectors and
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. This PhD project is set within the Fusion Engineering CDT at The University of Sheffield. Students will receive a 3-month training programme in fusion engineering at the start of the course, delivered across
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for a Scholarship from the University of Sheffield but should note that competition for these Scholarships is highly competitive: https://www.sheffield.ac.uk/postgraduate/phd/scholarships Funding Notes
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-learning enhancement approaches in a more user-dependent manner. The project will be based at the University of Sheffield and co-supervised by experts from both Universities of Sheffield and of Salford