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Field
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this overall aim, the student will Employ computer programming methods to determine the occurrence of Alzheimer disease in obstructive sleep apnoea patients using previously collected clinical data and Perform
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that are not seen in any other material. This project combines cutting-edge sampling techniques with machine-learned potentials for accurate phase predictions, offering considerable opportunity for method
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to develop forecasting models. The use of machine learning methods for demand modelling could also be considered. The models that are developed will be implemented in a modelling tool which could be used by
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responsibility for the design and development of teaching and learning material and the delivery these across a range of modules within Early Modern History, including the third-year Special Subject ‘A New
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calculations of well-characterized 2D materials, simulations of electron microscopy images, and machine learning methods to reconstruct the 3D atomic positions of materials from a 2D microscopy image. The
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Applications are invited for a PhD studentship in the Centre for Human-Computer Interaction Design, based in the Department of Computer Science. The successful candidate will undertake PhD research
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Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn more: The Dynamics Research Group: drg.ac.uk Digital Twinning Interest Group
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of (or aptitude to learn) quantitative data analysis and coding (e.g. R). Or a background in computer or data science who can demonstrate their ecological or natural history knowledge. Candidates should have a