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ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling to pioneer innovative sealing solutions. What We Offer Full 4-year Funding for UK applicants
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for downstream tasks. In this project, you will develop novel unsupervised machine learning methods to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a
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Form (see below) After submitting your Personal Statement, CV, transcripts, samples of writing and references through the application portal, please complete and email a copy of the NWSSDTP Equal
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physical and numerical modelling. Feel free to reach out to the project supervisors if you have any questions. Entry requirements: The ideal applicant will be enthusiastic and self-motivated with a first
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. Using gastruloids as a model system with which to study GAG structure/function relationships. Generating gastruloids from induced pluripotent stem cells (iPSCs) to create in vitro models for studying
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simulation study of light matter interaction, digital twin enabled process development and life cycle assessment will be researched. Opens: Immediately Deadline: 08/08/2025. Duration: 36 months Funding: Funded
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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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to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
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, upon receiving applications and rank them in priority order. The University of Manchester will provide CSC and each qualified candidate with a copy of the offer letter. After receiving the offer letter