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devices for medical imaging and reaction monitoring, as well as for the development of sustainable photocatalysts. In this role you will develop machine learning (ML)-accelerated quantum mechanics in
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Location: Central Cambridge We are seeking a highly motivated Research Assistant/Associate in Machine Learning to join an interdisciplinary project at the University of Cambridge focused on machine
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emergency responders. By combining global landslide data, innovative machine‑learning methods, and new ways of representing runout, the research will produce faster and more reliable nowcasts for use
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, including Machine Learning & Artificial Intelligence, Colour & Imaging, Computer Vision, Graphics, Data Science, Health Computing, Computational Biology, Cyber Intelligence and Networks. We collaborate with
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knowledge. This project requires specific and essential skills; however, these can be learnt throughout the PhD and with help from supervisory team. These may include: · Difficulties with learning how
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simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
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, machine learning, and photonics. Be part of a multidisciplinary research team spanning science and engineering. Access state-of-the-art laboratories and high-performance computing facilities. Gain
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About us: The applicant will join the Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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: • Knowledge of fluid dynamics, especially experimental methods in atomisation and sprays. • Programming experience (e.g. Python, MATLAB or similar). • Experience with data analysis, machine learning
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on epithelial barrier integrity, inflammation, and host transcriptional responses. The project offers interdisciplinary training in bioinformatics, advanced statistics and machine learning, anaerobic microbiology