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models for high-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available
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, Modeling, and Perceiving the Combinatorics of Groove-based Rhythms, funded by the Research Council of Norway. The project is affiliated with RITMO Centre for Interdisciplinary Studies in Rhythm, Time and
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. The candidate shall take part in the research group on “Statistical models for high-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models
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rationale multi-cancer approach and modern genome-wide methods for regulatory genomic features and chromatin architecture. We utilize a wide range of cell-based models, organoid systems together with cutting