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. The candidate must have or be willing to learn computational methods for data analysis. The studentship covers fees at the Home rate, International fees are not covered. How to apply You must apply through
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Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy" Research theme: "Materials Characterisation" "Data Science and Machine Learning in Materials" "Plastics
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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. Experience in computer programming and design would be essential. Experience in one or more of the following: Image analysis Matlab and Python programming Machine Learning Fluency and clarity in spoken English
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combines hands-on training, cohort-based learning, and cutting-edge research, preparing graduates for careers in academia, industry, startups, and beyond. We welcome applicants from the Physical Sciences
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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may also explore embedding these new computational methods into optimisation and machine learning contexts. The new computational techniques developed will be geared towards the following key
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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project aims to explore techniques that could facilitate experts in the elicitation of priorities. One possible direction could be to use the technique of Inverse Reinforcement Learning (IRL) [2], [3]. IRL
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung