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Field
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distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By establishing an understanding of "what normal looks like", these models will detect deviations from the norm and
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of peatlands under future climate change, incorporating projected outcomes from restoration activities and the identification of environmental tipping points from mechanistic modelling of species distributions
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to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By
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component modeling and testing. Knowledge or classwork related to energy systems with design and computational model analysis using engineering software will be necessary. Demonstrated research capability and
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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1 and 2 and NQCC Testbed programme, will tailor the developed benchmarking approaches to error-corrected as well as distributed quantum computers, addressing the need for scalable benchmarks
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would be in addition to the normal employment and academic requirements of the student’s graduate program. Employment in this position would not reduce the work required as part of the graduate program
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, distributed ledgers) Desirable: Experience with generative AI (e.g. LLMs) Interest in Human-Computer Interaction Interest in privacy enhancing technologies (PETs) Other: Experience in presenting or preparing
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Application deadline: 15/08/2025 Research theme: Computer Science No. of positions: 1 Eligible for: UK This 4-year PhD project will be funded by DLA studentship and is open to UK students