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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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functional data ”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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a spatially explicit predictive model for Everglades vegetation dynamics in response to major drivers. The major objectives are to explore the distribution models that discriminate among prairie and
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an inclusive community that is respectful and fair for all. Find out more about the benefits of working at the University and what it is like to live and work in the Durham area on our Why Join Us
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closed-world assumption to incorporating open-world perception and action capabilities. The primary objectives of your project/research include: Enabling robots to detect known objects while identifying