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candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of molecular data in cancer genomics. The position is connected
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”, 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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construction phylogenetic comparative analyses with Bayesian computational tools The applicant must have the ability to work independently and in a structured manner and must be willing and able to cooperate
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ethnomycology or ethnobiology large-scale (ethnographic) database construction phylogenetic comparative analyses with Bayesian computational tools The applicant must have the ability to work independently and in