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in colorectal cancer. You will be responsible for developing spatially-resolved models of metastatic outgrowth in the liver which account for interactions between stromal, immune and tumour cells. You
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strategic programme. Through multiomic and spatial biology exploration of temporally distinct samples from clinical trials and advanced biological models, an international consortium of leading colorectal
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automating geospatial workflows. Proficiency with GIS tools (e.g., QGIS, ArcGIS) for spatial analysis and visualization. Experience developing statistical or machine learning models to estimate fuel moisture
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our lab including single-cell transcriptomic analysis and cellular growth quantification in the plant model organism Oryza Sativa (rice) and beyond. The candidate will work here mainly as a cell and
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analyze and interpret multi-omic data to identify spatial patterns, cellular neighborhoods, and gene programs associated with drug resistance. Develop predictive models to infer tumor evolution and
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spatial network metrics. Strong quantitative skills, with experience in clustering analysis, data visualization, and statistical modelling. A research background in health-related topics. Demonstrated
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hampered by uncertainties about viable business models and reward structures. Your job This postdoctoral position is part of ReGeNL , a large national inter- and transdisciplinary research programme aimed
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4 Oct 2025 Job Information Organisation/Company CNRS Department Centre d'études spatiales de la biosphère Research Field Environmental science Biological sciences Geosciences Researcher Profile
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to colon cancer progression. The postdoctoral researcher will use a transgenic inducible colon cancer mouse model and organoids derived from this model. They will use various histology, molecular biology and
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. The Ravnskjaer lab is headed by Assoc. Prof. Kim Ravnskjaer and focuses on cellular crosstalk in the regulation of liver function in health and disease. For this we apply single cell- and spatially resolved