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Field
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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mathematics, physics, engineering or subsurface flow modelling. Enthusiasm, willingness to learn, and the ability to think creatively about complex physical systems are just as important as specific technical
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computing. These include computer graphics and geometry processing, computer vision and image processing, visualization and visual analytics, augmented and virtual reality, machine learning and deep learning
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systems, cartography, and remote sensing. Students acquire theoretical and practical knowledge, methodologies, and techniques for solving geographical problems. It encompasses scientific research and
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biosynthetic gene clusters and other molecular features relevant to natural product drug discovery Validating machine-learning and deep-learning models to predict the chemical structures and bioactivity
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
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engineering Knowledge of machine learning (deep learning) Basic knowledge of computer science or software development, e.g., using Java, Python, or C++ Good communication and information skills, goal-oriented
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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digital signal and image processing, IoT, cyber security, deep learning, and software systems. Applications in healthcare, multimedia, and sustainable urban environments are encouraged. School