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automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained to predict the probability that an occupation in the data-set is automated
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automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained to predict the probability that an occupation in the data-set is automated
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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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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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excellent academic record in computer science, economics or a cognate field. An Honours degree with H1 or equivalent is required for Graduate Research admission. An interest in game theory and in how
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excellent academic record in computer science, economics or a cognate field. An Honours degree with H1 or equivalent is required for Graduate Research admission. An interest in game theory and in how