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group belonging to the unit of surgery and oncology. Your mission The group performs research on colorectal and pancreatic cancer and is looking for assistance with histological data analysis for a
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cells from liver and blood. You will be exposed to advanced immunological methods such as high dimensional flow cytometry, multiplexed imaging (MACsima) and spatial transcriptomics (Visium). We
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heterogeneity of paraganglioma and childhood neuroblastoma by developing a new analytic and experimental approach based on spatial transcriptomics and single-cell transcriptomics with integrated mass spectrometry
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should be familiar with and be able to demonstrate experience with the analysis of single cell or spatial genomics datasets in R or Python programming. Fluent written and spoken English is mandatory. What
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at international conferences The successful candidate will apply and develop protocols including in vitro and ex vivo culture (2D and organoid), size exclusion chromatography, nanoparticle tracking analysis, flow
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. Computational candidates should be familiar with and be able to demonstrate experience with the analysis of single cell or spatial genomics datasets in R or Python programming. Experimental candidates should be
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the design and implementation of tailored computational workflows for the analysis of single cell and/or spatial transcriptomics data. Excellent communication and presentation skills as well as a collaborative
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the pathophysiology of radiation-induced brain damage. In this context, the candidate is expected to combine and interpret previously attained data from single-cell RNA sequencing, spatial transcriptomics and
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the transcriptomic profiles of genetically traced intervertebral disc cells and adipose tissue cells. The research work includes single cell/nucleus data analysis, confocal imaging, immunofluorescence
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or more of the following areas: differentiation of human IPS cells (2D or 3D), co-cultivation of neural cells, cell engineering (CRISPR and virus work), single cell/nuclei/spatial omics methods (RNAseq