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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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You will be collecting, analysing, and presenting data throughout the study informing the intervention and app and contributing directly to the education/instructional videos contained within them
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programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full-time). More information on the department and the programme is available at the departmental prospectus page here: https://www.kcl.ac.uk
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for automotive applications” BCAST is a specialist research centre in metallurgy with a focus on processing of metallic materials for lightweighting applications. See www.brunel.ac.uk/bcast for more information
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conducting the qualitative interviews with patients and analysing the interview data. You will be presenting that data to the study team at regular meetings and contributing to the intervention and app
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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-time). More information on the department and the programme is available at the departmental prospectus page here: https://www.kcl.ac.uk/neuroscience/about/departments/neuroimaging https://www.kcl.ac.uk
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automated rankings. The research includes real-world validation using university admissions data and will contribute to the broader fields of AI in education and ethical decision-making. This PhD research
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological