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) , Department of Biostatistics, Institute of Basic Medical Sciences (IMB), University of Oslo (UiO), Norway. The candidate shall take part in the research group on “Statistical models for high-dimensional and
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deficiencies may impact neural development and transcriptomics in rodent models. The selected candidate will be hired at the University of Oslo and join a collaboration at the Nordic EMBL Partnership institutes
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estimators, or machine learning) or other advanced statistical modelling. Advanced programming skills in Stata, R, Python or a similar software. Strong academic background with publications in international
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Fellowship for an interdisciplinary project combining Molecular Biology and Systems Neuroscience to study how sleep deficiencies may impact neural development and transcriptomics in rodent models. The selected
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cholangitis (PSC). Several features make PSC an intriguing model disease; more than 80% of the patients have inflammatory bowel disease, for which the link with the biliary inflammation is poorly known, and the
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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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psychiatry on longitudinal multimodal data, to fit and validate prediction models. Perform quality control and imputation of genotype data from relevant datasets, including international and Norwegian samples
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Develop and apply machine learning techniques and statistical analyses, including digital twin methodology, to fit and validate prediction model. Perform quality control and imputation of genotype and
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collaboration with the theorists involved. The postdoc will construct and use 3D printed model porous media. The analysis will entail extensive use of image analysis techniques such as Particle Image
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legal issues such as the rights to AI-assisted and AI-generated works and compensation for use of existing works in AI model training. In light of this ongoing transformation, it is imperative