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trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data. The successful candidate will contribute to understanding how modern machine
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ecology that challenges Western narratives and explores alternative ways of thinking and living with weeds by learning from traditional knowledges in their places of origin; a multispecies geography that
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supportive culture that fosters knowledge exchange, learning, creativity and scientific excellence. The PI, the group, the Department and university-wide initiatives (e.g., the Durham Centre for Academic
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partners. 7. Knowledge, or willingness to learn, of the protected characteristics of the Equality Act 2010, and how to actively ensure fair and equal treatment. 8. To have worked on theoretical