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marine sciences, biological oceanography, ecology, or computer sciences. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a
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written English is required. A real passion and commitment for research. Desirable criteria are: Knowledge of a variety of deep learning architectures and methods. Knowledge or past work on explainability
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to learn laboratory methods for analysis of relevant BGC parameters. Training: You will be based in the Polar Oceans Team at British Antarctic Survey, a highly active research team focused on both
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-3413 ), 4-Limited flight data for adaptive methods (doi.org/10.1016/j.geits.2022.100028 ), and 5- Failure to use a robust state estimator to increase robustness of EMS in eVTOL, have not been filled by
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Primary Supervisor -Prof Michal Mackiewicz Scientific background Marine litter is a key threat to the oceans health and the livelihoods. Hence, new scalable automated methods to collect and analyse
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challenges which experimentalists must consider – computer simulations of molten salts are therefore a very valuable guide to efficient experimentation. Molten salts have been well-studied using classical
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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years. The School consists of the Department of Psychology, the Department of Languages and Intercultural Studies, the Department of Research Methods and Practice, and Edinburgh Business School. Our
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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develop novel approaches that integrate uncertainty estimation and confidence-aware predictions, enabling models not only to classify species but also to quantify their reliability. Such methods are crucial