337 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD scholarships in United Kingdom
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of separating fire-induced signatures from natural environmental variability (weather, canopy changes, tree motion) and fluctuations in the SoO sources themselves. Machine-learning methods will help improve long
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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for Robotics in the School of Engineering. The Institute brings together multidisciplinary researchers to explore all aspects of robotics, automation, autonomous systems, AI and smart machines. The studentship
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biodiversity support, cooling, air quality regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue
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to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative
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Computer Science or MSc in related field. Skills Knowledge of programming, Computer Vision, Machine Learning, or related discipline. Experience with Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow
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environments: The C-Wild Warrington lab (Ecology and Conservation ) and the Machine Learning and Robotics research group (Artificial Intelligence, Data Analysis and Systems ). This will provide
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-grade experience that employers value. The journey You'll develop machine-readable privacy rules, build core functionalities that audit and explain data-sharing decisions, prototype agent systems showing
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning