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environments, and distributional shifts. The research will combine probabilistic modelling, network-based representations, and modern AI methods to enable scalable and interpretable decision-making in complex
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Location: Central Cambridge We are seeking applications for a PhD position in AI in proteomics as part of the Horizon Europe MSCA Doctoral Network, ProtAIomics. This brings together laboratories
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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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. Two PhD studentships are available to address one or more of the following scientific challenges: 1. Mechanical Integration Structural and functional integration requires the development of novel
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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