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recognized, peer-reviewed journals This work will be focused on large-scale studies encompassing multiple species and locations outside the breeding period. Qualifications You must hold a PhD in ecology or
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Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference
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when multiple data sources are available, mostly tailored to the case of dynamic sequential inference and probabilistic recommender systems. The position is connected to the project “Bayesian Rank-based
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qualifications: • Strong background in modelling, including spatial and temporal/dynamic modelling, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams
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, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams • Experience with data science and biodiversity informatics, in particular handling of scientific collection