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, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging
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of support they receive, or fail to receive, during the migration process. A total of four PhD candidates will work on the project together with an international and multidisciplinary team of senior
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for Biostatistics and Epidemiology at UiO, the Norwegian Computing Centre (NR) and the ML group at UiT, with members from the departments of Physics and Technology, Mathematics and Statistics, and Computer
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the migration process. A total of four PhD candidates will work on the project together with an international and multidisciplinary team of senior researchers and civil society partners. The PhD candidate
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equivalent in a quantitative discipline such as statistics/biostatistics, data science, mathematics, physics or similar (with documented knowledge in statistics). Master’s degree with an average grade of B
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spatial structures, physical laws, high-dimensional imaging, and clinical covariates. Apply these methods to spatial transcriptomics and fluorescence imaging data to gain a more precise understanding of
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, or physical adjustments, or other practical measures. If you have an immigrant background, a disability, or CV gaps, we encourage you to indicate this in the job application portal. We always invite at least
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Master’s degree (120 ECTs) in neuroscience, biology, medicine, computer science, physics or engineering, or closely related fields. Minimum grade B (ECTS grading scale). The Master’s degree must include a
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adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures. If you have an disability, we encourage you to indicate
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novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws, high-dimensional imaging, and clinical