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, including digital twin methodology, to fit and validate prediction model. Perform quality control and imputation of genotype and ´omics data, as well as processing of neuroimaging data from relevant datasets
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is connected to the project “Bayesian Rank-based unsupervised Integration of multi-source Data in cancer Genomics and the digital Economy (BRIDGE)”, recently funded by the Research Council of Norway
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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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of molecular data in cancer genomics. The position is connected to the project “Bayesian Rank-based unsupervised Integration of multi-source Data in cancer Genomics and the digital Economy (BRIDGE)”, recently
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be solicited. You should indicate your relation to these persons. Please do not submit any recommendation letters before we contact you and explicitly ask you to. Please note that all documents should
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writing skills proficiency in programming and scripting languages (e.g., R, Python and/or Matlab) experience with data processing and statistical analysis, including familiarity with relevant statistical
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, bioinformatics, or computational biology. Proficiency in programming and scripting languages (e.g., Python, R, Matlab). Experience with data processing, large-scale genomic and neuroimaging data, and statistical
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institute. Our activities follow the clinical activity at the hospitals and are spread across a number of geographical areas. For more information: Division of Surgery, Inflammatory Medicine and