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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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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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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
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and has a large group of collaborators. You will be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn More: The Dynamics Research Group
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) Familiarity with machine learning models, for example, large language model (Desirable) *This opportunity will cover UK/Home fees. Overseas students who wish to apply would need to be able to finance
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in computer vision would be beneficial but not essential; determination, curiosity, and a willingness to learn are key attributes we value. Applicants with alternative qualifications, industry
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textiles, materials, soft robotics, sports, healthcare, machine learning and AI, with globally leading industrial and academic partners. Your Project The project focusses on the healthcare and sports
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techniques for multivariate curve resolution, together with physics-informed AI to overcome Nuclear Decommissioning Authority (NDA) data analysis challenges. Previous machine learning (ML) uses ‘out-the-box
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technologies to enhance vehicle performance and safety, including the creation of generalised machine learning training processes. Additionally, AI-driven adaptation strategies will be investigated to enable
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful