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Primary supervisor Thanh Thi Nguyen Research area Data Science and Artificial Intelligence This project aims to develop a computer vision system capable of detecting and classifying domestic
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their ability to generalise across different clinical applications. Inspired by the success of foundation models in natural language processing and computer vision, this project seeks to develop
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would be a plus) Experience in statistics/computer vision/machine learning/robotics Outstanding academic output documented via journal/conference publications in the relevant fields Ability to program
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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NMT models where sufficient parallel corpora are not available (eg [1,2]). This project investigates methods to enable high performing NMT in low-resource scenarios. [1] Neural Machine Translation for
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NMT models where sufficient parallel corpora are not available (eg [1,2]). This project investigates methods to enable high performing NMT in low-resource scenarios. [1] Neural Machine Translation for
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background in machine learning, deep learning, artificial intelligence, or computer vision Strong Python programming skills Experience with at least one deep-learning framework, preferably PyTorch An
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computer programming background who has an interest in ecology and biodiversity conservation, or an ecologist with computational modelling experience (e.g., using R, Python, Matlab). Project funding
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will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly generated data. The world will see all too many changes
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will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly generated data. The world will see all too many changes