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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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successful candidate will work in the AI in Medicine Lab, applying machine learning to cutting-edge problems in cancer genomics, transcriptomics, spatial transcriptomics, and large-scale bioinformatics
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methods to biological and clinical research datasets. Primary responsibilities include analyzing bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics data; developing and maintaining reproducible
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inflammatory systems; applying cutting-edge multi-omics technologies such as single-cell sequencing and spatial transcriptomics to translational research; and developing novel therapeutic strategies and
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and chemical composition analysis of iron artifacts, slags, and ores GIS spatial analysis, statistical analysis, and network analysis of iron production Other Participation in ensuring operational and
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agenda of fundamental and applied research on research questions such as (1) the spatial, structural and functional characteristics of ecosystem elements; (2) the integrity of natural and human-produced
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the causal circuits driving the development and the functional specialisation of the largest macrophage population in the body: the liver-resident Kupffer cells. You will next develop Spatial CRISPR screens in
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and histological analyses, comprehensive animal behavioral testing, muscle and nerve electrophysiology, the use of genetically modified animal models, as well as spatial transcriptomics and proteomics
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private companies and actors from the healthcare sector. Several key infrastructure facilities are available, including specialized laboratories for spatial omics, mass spectrometry, flow cytometry, and
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research and teaching will use spatial data and modelling to explore alternative futures of land use at local, European and global scales. You will show policy makers and different stakeholder groups