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, including scRNA-seq, spatial transcriptomics, methylation profiling and integration of molecular data. Experience in translational biomarkers, target-engagement studies (PD), analysis of human biological
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remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning
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. This 4-5-year project is supported by an NIH R56, the HNC SPORE, and other research funding. The postdoc will investigate the spatial and functional relationships between intratumoral bacteria and immune
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, and data analysis. Additionally, the scientist will also play a pivotal role in collaborating with other cores and shared resources to integrate spatial metabolomics datasets with high-dimensional data
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in the past, or that incorporates MAIHDA with other methods (e.g. policy analysis or spatial analysis); development of training resources, for instance an R Shiny app that helps researchers make good
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develop the urgently needed system understanding, data analysis tools, and forecasting models for science and expert users, and co-create common ground among stakeholders for future-proof coastal management
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interactions and for forming charge-transfer excited states with spatially separated frontier orbitals. The project will combine organic synthesis, COF materials chemistry, structural characterization
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and proteomic profiling. Qualifications and personal qualities: The applicant must hold a Norwegian PhD or an equivalent degree within neurobiology/ tumor biology, or equivalent in a relevant field of
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when neuromodulation by acetylcholine, dopamine, noradrenaline and serotonin occurs in the hippocampus during spatial navigation tasks in mice designed to manipulate the type and degree of error and
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sustainable in-house expertise Your Profile: PhD in any field with strong bioimage analysis component, computer science, data science, computational biology or a related field Several years of relevant