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Federated Learning (FL) allow parties to collaboratively analyze a collection of data partitions where each data partition is contributed by a different party (such as banks, or law enforcement agencies). Two
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that they have demonstrated in a laboratory environment, expanding on the breakthroughs and key learnings discovered. Number Of Awards 1 Start Date 17th September 2024 Award Duration 4 years Application Closing
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the data and apply machine learning techniques to identify process efficiency improvements and enable prediction across scales for a given biological process. The PhD project will develop, construct and
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. Strong programming skills, preferably Python, Matlab, or R. Experience with one or more of hardware-programming, cyber physical/electrical systems, privacy-enhancing technologies, machine learning, signal
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systems, privacy-enhancing technologies, machine learning, signal processing. Good communication skills, especially in written English. Strong work ethics. Ability to think creatively and work independently
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developed. During your PhD, you will develop theoretical expertise in the field of solid electrolyte technologies. You will learn how to carry out atomic-scale simulations of a variety of topical solid
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studied at degree level or higher in the UK or lived recently in the UK. Distance learning at a UK university or study at a UK branch campus in another country will also be considered as studying in the UK