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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian
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technologies for target and TCR identification, and to couple clinical immunotherapy trials with penetrating mechanistic analyses. The research is performed in an interdisciplinary and translational program. The
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-imaging Experience with correlative optical microscopy methods, e.g., combining quantitative phase microscopy with fluorescence microscopy. As the target applications involve organoids and viruses
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mapping epigenetic aberrations that enable identification of novel cancer targets. This project funded by the Norwegian Cancer Society focuses on the mechanisms underlying chromatin interactions and gene
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. The project targets modeling formation dry-out and salt precipitation during CO2 storage. The candidate will work on developing numerical models for salt precipitation at pore- to continuum-scale, with special