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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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. The successful candidate will develop advanced skills in multi-modal sensor fusion, signal processing, machine learning, and integrity assessment, as well as transferable abilities in critical thinking, project
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the Safety and Surveillance Group and the wider Agency. The successful candidate will have: A PhD in Computer Science, Statistics, Machine Learning, Data Science or a similar quantitative discipline or
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reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
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experience in astronomical data analysis activities, coupled with use of machine learning approaches to data validation, a good practical knowledge of scientific algorithm development and a PhD degree in a
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: Autonomous Systems and robotic platforms Agricultural Robotics and precision agriculture technologies Artificial Intelligence and Machine Learning applications Computer Vision and sensor integration
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
AI-assisted adversarial attacks. You will work on topics such as cybersecurity, intrusion detection, adversarial machine learning, industrial automation, digital twin technology, and reinforcement