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in implementing, testing and validating complex minimisation algorithms that can be used for adaptive trials. Application & interview 8 Experience of collaborating on successful research proposals
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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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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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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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Interplay between Algorithms and Combinatorics
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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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. 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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@sheffield.ac.uk Our vision and strategic plan We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window). What we offer A minimum of 41days annual leave including bank
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(DK) University of Vienna (AT) Leipzig University (DE) Friedrich-Schiller-University Jena (DE) TU Vienna (AT) The University of Sheffield (UK) European Molecular Biology Laboratory (EMBL) BASF SE (DE