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user and stakeholder engagement. The candidate will be embedded in a multidisciplinary research environment combining expertise in machine learning (ML), numerical modelling, satellite remote sensing
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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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computational modeling. The postdoctoral candidate will: Analyze quantitative molecular and imaging data produced by other members of GENESIS. Develop new machine learning models to identify gene regulatory
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quantitative molecular and imaging data produced by other members of GENESIS. Develop new machine learning models to identify gene regulatory mechanisms involved in the physical mechanisms of cellular self
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Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The research group on statistical models for high-dimensional and functional data is part of the larger and active research
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separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement rule-based methods. For more
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computational modeling to identify bacterial strains and metabolites that promote or hinder probiotic establishment. By combining multi-omics data with systems biology and machine learning approaches
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one or more of the following: data curation, digital signal processing, music information retrieval, audio source-separation, audio analysis, statistical modeling, machine learning, and advanced
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positions within their disciplines. A career plan shall be developed for the Postdoctoral Fellow, specifying the competencies the Postdoctoral Fellow should acquire. UiO is responsible for following up
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Fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the Postdoctoral Fellow has access to career guidance throughout the postdoctoral term. If the Postdoctoral