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We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only
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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate
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to manage time and work to deadlines Ability to critically evaluate publications, experimental design, protocols, and research findings. Excellent interpersonal, oral and written communication skills Ability
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opportunity to gain experience in local government and will ensure relevant findings impact local policy. PhD studentship: The successful student will be supported to develop critical literature reviews and a
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with children and an interest in educational practices, speech and language development, and outdoor learning is highly desirable. Familiarity with programming and data analysis tools is also preferable
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, and outdoor learning is highly desirable. Familiarity with programming and data analysis tools is also preferable as the PhD will involve some advanced quantitative data analysis, although support will
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with children and an interest in educational practices, speech and language development, and outdoor learning is highly desirable. Familiarity with programming and data analysis tools is also preferable
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(Dr Jun Jiang) (2) In-situ formability, microstructure analysis and forming process optimization (Prof Li-Liang Wang) (3) Crystal plasticity modelling to understand how microstructural features caused
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relevant subject, or be able to demonstrate equivalent experience in a setting involving knowledge of and critical reflection on relevant topics. There is scope to take a more historical/digital/practice
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Europe. Recently awarded the prestigious Marie Skłodowska-Curie Actions Doctoral Network grant, the AUREUS network is dedicated to addressing the critical global challenge of multidrug-resistant