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immunotherapy with graph neural networks trained on spatial single-cell tumor microenvironment (TME) data from non-small cell lung cancer (NSCLC). Using high-dimensional datasets, you will learn bi-directional
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, spatial data, and perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join
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point for computational biology, delivering bespoke bioinformatics support and training across genomics, transcriptomics, spatial biology and AI/ML projects. We co-lead the Applied Bioinformatics MSc, run
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tumor microenvironment (TME) following immunotherapy using state-of-the-art single-cell and spatial profiling approaches. Our group studies ecological mechanisms in early lung cancer development and
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the built environment. The Postdoctoral Fellowship Program, made possible via our Strategic Partnership with Halter Group AG , funds a two-year postdoc position annually over 5 years. The goal is to advance
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to the Director of the HAB and working in close partnership with the Spatial Biology Facility, you will lead the development and optimisation of high-resolution spatial biology and multi-omics data analysis
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disease mechanisms from single-cell and spatially resolved multi-omics data. You will work within an international and interdisciplinary group of scientists to better understand and treat diseases (for more
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analysis. Experience with spatial assays and/or clinical data is preferred but not required. ● You have experience with in vivo or in vitro models, preferentially relevant to lung biology. ● Excellent
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Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country Norway Application Deadline 1 Nov 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week
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of agroecological farming in EuRope ), funded by the Research Council of Norway. About the project/work tasks: As a postdoc within a large international and interdisciplinary team you will use spatial modelling