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Project title: Developing and Evaluating Interpretable Approaches for Human-Centered Machine Learning.Project description: Approaches in interpretable machine learning offer promise in understanding
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the latest advances in AI to identify factors in pregnancy, labour and in the early neonatal period that represent increased risks for CP. We will develop novel AI algorithms for the analysis of physiological
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evaluation. Previous knowledge of belief/trust for vehicular cooperative perception is a distinct advantage as is experience with algorithm development and networking simulation. Candidates should have
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development and training dataset generation. The processed training datasets will be used to develop classification algorithms, in conjunction with Swisens, to identify different fungal spores in near-real-time