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chemically active drop. These microscopic drops use chemical energy from an ambient fuel to swim and explore their surroundings. Their appeal lies in their ability to be manufactured in large numbers via
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Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A
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and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
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This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a
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3 Year, full-time PhD studentship Eligibility: Open to home, EU and international students Bursary p.a: £21,805 University fees and bench fees: This studentship will cover university fees
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Supervisor: Dr Tim Halim Course start date: 1st October 2027 Project details For further information about the research group, please visit our website at https://www.cruk.cam.ac.uk/research-groups
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the landscape of novel target expression, quantify its heterogeneity, and the contribution of tissue architecture as a determinant of expression profiles. This project will involve large scale data processing and
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. There is also a need for accounting noise in Deep Learning models and quantifying uncertainty in real-world applications. This PhD studentship (scholarship) leverages large-scale Earth Observation data
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training and collaboration across historical, social science, legal, and data science methods, including Earth Observation analysis and the large-scale analysis of survivor narratives. Applicants proposing
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science