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Field
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qualifications You have graduated at Master’s level in computer science, computer engineering, human-computer Interaction, media technology, visual learning and communication, or closely related fields
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Would you like to work at the intersection of transportation, robotics and machine learning
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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Eligibility Criteria You must have, or expect to gain, a minimum 2:1 Honours degree or international equivalent in a subject relevant to the proposed PhD project (inc. computing, mathematics, engineering etc
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automata, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
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the investigation and realization of improved microwave probe design, data processing, and visualization techniques to provide a robust method of data analysis, flaw characterization and sizing. AI/machine learning
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corresponds to full-time PhD education for four years. Read more about being a Doctoral student at the Faculty of Medicine here . Requirements Master’s degree in biomedical engineering, biotechnology
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab