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8th June 2025 Languages English Norsk Bokmål English English Postdoc - Computer vision for sustainable forest management Apply for this job See advertisement Key information SmartForest is a center
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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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biomarkers, clinical, and cognitive variables, genotyping and sequencing data, and MRI brain imaging data on patients with severe mental disorders. In addition, we work closely with national population cohorts
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employees and 43,000 students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here . ... (Video unable to load from YouTube. Accept
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data, and MRI brain imaging data on patients with neuropsychiatric and severe mental disorders. In addition, we actively collaborate with large international consortia, particularly the Psychiatric
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for academic development.- Potentially opportunities for international research visits through scholarships provided by the Research Council of Norway.- Flexibility in how you structure your work tasks
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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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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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transplantation and it is very difficult to treat. In this project our aim is to understand the underlying pathology of aGVHD to avoid and/or improve treatment of this potentially life-threatening complication
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. Required qualifications The successful candidate must have: Master’s degree/Cand.psychol. degree in psychology. PhD in a relevant field, with a dissertation focused on a topic within developmental psychology