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Field
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, PhD students, clinicians and computer scientists who will all support the studentship. The successful student will be further supported by members of the wider 4th floor research groups and existing
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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PhD programme within QMUL’s Wolfson Institute of Public Health, under the supervision of Dr Giuliano Russo (WIPH) and Prof. Pietro Panzarasa (School of Business and Management). As part of the project
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, providing access to the full programme of research and knowledge exchange and all the opportunities that this affords. The centre was launched in November 2021, funded by a £10 million award from the ESRC
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Overview Location: College Lane Campus Programme Description The Centre for MoDDD at the University of Hertfordshire invites applications for a PhD candidate to join a 3-year QR funded research
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Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name & email address Dr. Ping Lu: p.lu@leeds.ac.uk