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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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(Jonathan.rossiter@bristol.ac.uk ) For questions about eligibility and the application process please contact Engineering Postgraduate Research Admissions admissions-engpgr@bristol.ac.uk
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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with participants to deliver measures concerning people’s experiences of the diagnostic process, their access to services and their general well-being and life quality. The positions are ideal for people
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metagenomics, host transcriptomics, and clinical metadata. Training will be provided in ONT data processing, differential expression and abundance analysis, and bulk or single-cell RNA-seq. The project will use
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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, this interdisciplinary project will couple mathematical models of earthworm movement, stochastic models of the measurement process and designed experiments to improve earthworm detection. Project This project will work
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at higher risk offered PSA blood tests which are not definitive. Our research aims to develop an image-based approach to screening, combining PSA testing with MRI to better identify aggressive cancers