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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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(or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject area: Medical imaging, biomedical engineering, computer science & IT
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about computer data analysis and willing to learn. Laboratory training will be provided but a steady hand is needed for accurate small volume pipetting. You will be working in a team and expected to
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understanding of engineering mechanics and mechanical behaviour of materials. Knowledge of irradiation damage, computer modelling for nuclear materials, or steel metallurgy would be advantageous. Potential
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for the company, which will open new markets and opportunities. This PhD covers a wide range of skills and so it is essential the candidate has a 1st degree in electronics, computing or aerospace/space technology
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techniques that are useful for the modelling of many real-life systems. These include the development and analysis of stochastic models, computer simulations, differential equations, statistical inference
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The School of Computer Science and Electronic Engineering (CSEE) is delighted to announce a fully funded PhD Studentship covering Home fees of (£5,006 for 2025-26) plus stipend. Stipends will match
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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programming for hardware control, data acquisition, and automation, computational reconstruction, data correlation. Interpersonal and leadership skills as required for interdisciplinary collaborative research