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to also improve and scale the process. We have made major contributions in this area, including the use of Machine learning to discover new cryoprotectants [Nature Communications 2024, 15, 8082
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composites To propagate uncertainty in material behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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for computer, lab, and fieldwork costs necessary for you to conduct your research. There is also a conference budget of £2,000 and individual Training Budget of £1,000 for specialist training Project Aims and
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systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural language understanding (to interpret instructions), and action generation (to respond), enabling robots
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, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the
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sluggish diffusion kinetics of HEAs make them excellent candidates for resisting oxidation and corrosion in high-temperature steam. Guided by thermodynamic modelling and machine learning, we will identify
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(CHF), tailored to complex geometries typical of fusion reactor cooling systems. Compile a comprehensive dataset of boiling parameters to support machine learning-based analysis of two-phase flow
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cell and spectroscopic analysers. Programming (e.g., R, Python) and machine learning for advanced atmospheric time-series analyses. Skills for presenting research at conferences and writing peer-reviewed
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis