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Field
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biomass to energy with carbon capture and storage (BECCS) etc. Training and Development Through our research training programme, you will be able to: Develop a network with doctoral researchers, academia
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, healthcare, public-sector and industry collaborators. This environment will support the candidate in moving beyond the development of an AI model to consider responsible implementation, clinical relevance
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. Qubit counts have risen year after year, driven by advances in fabrication, control electronics and system integration. Quality, however, has not kept pace. Today's qubits remain noisy, short-lived and
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for infrastructure platforms in minerals-to-green metals transformation. It will suit a candidate interested in combining experimental materials science, advanced characterisation, and data-driven modelling to develop
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biology or a quantitative discipline, such as physics, engineering or applied mathematics, with expertise in programming and an interest in developing AI-driven computational tools for biological data
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. The Opportunity This interdisciplinary PhD project between IT and the social sciences will explore the development of computational approaches for detecting and analysing misogynistic backlash ecosystems across
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to developing methods for iPSC culture, 3D cell models, and stem cell differentiation within the field of complex tissue regeneration. In this PhD project, you will work at the interface of stem cell biology
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integrated early in development to ensure the materials are safe, affordable, and user-friendly. The project will also explore behavioural drivers, incentives, and innovative business models to stimulate
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. The main activities include: Designing machine learning models that can detect unusual, unsafe, or attacked operating conditions. Developing data-driven models that capture how faults and attacks spread
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assurance, data science, data-driven modelling, digital manufacturing workflows, and Digital Product Passport B.3 Hands-on experience in machine learning, ontologies and knowledge graphs, IIoT and digital