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models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code and documentation. The successful candidate will join Oxford's
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theoretical modelling. The project will focus on self-learning active mechanical networks, but will be tailored to align with the interests and expertise of the successful candidate - we will mutually ensure
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further appears in the approximation of various dynamical problems by tensor networks and neural networks. In all these cases, the parametrization is typically irregular, meaning that the occurring linear
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PhD Studentship in Cardiovascular Development: “Pharyngeal endoderm transcriptional networks regulating aortic arch artery development and malformation”, funded by the British Heart Foundation
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This 3.5-year PhD project is fully funded; students who are eligible to pay tuition fees at the Home rate are eligible to apply. The successful candidate will receive an annual tax-free stipend set
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computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly
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microenvironment, and which states ultimately suppress or promote tumour development. The PhD project will investigate the molecular and epigenetic mechanisms underlying transitions between preneoplastic cell states
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laboratory and professional development training programme and be supported to develop your networks within the UK geoscience and nuclear sectors. Due to funding restrictions, this studentship is only
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the University of Edinburgh, UCL and University of Bristol, and you will have the chance to work with researchers across our network at other UK universities. The PhD studentship would be co-located with
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to the major arteries supplying the heart and body, are poorly understood. This PhD project will investigate how the pharyngeal endoderm, a specialised embryonic tissue, regulates aortic arch artery development