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-cell and bulk transcriptomics, mutant screens and transformation approaches to identify signalling pathways and regulatory components. You will analyze data and integrate multi-modal datasets by applying
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, enabling in-depth profiling of tumour biology. A major component of your work will be to establish intratumoral heterogeneity maps using spatial proteomic profiling, including the use of laser capture
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for GIS, cartographic maps, geodata infrastructures and geo-analytical workflows; some experience with AI and machine learning methods to label texts (NLP) or data sources; strong programming skills (e.g
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implement proteomic workflows tailored for highly limited, heterogeneous samples, enabling in-depth profiling of tumour biology. A major component of your work will be to establish intratumoral heterogeneity
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workflows; some experience with AI and machine learning methods to label texts (NLP) or data sources; strong programming skills (e.g., Python, RDF) and some skills in web-based data retrieval; good English