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omics-based approaches. Interest in spatial biology, single-cell/spatial omics technologies and the integration of tissue-based, molecular and clinical data. Basic computational and data-analysis skills
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qualifications will be considered an advantage: Knowledge of C++ and C#. Experience with spatial transcriptomics and other spatial omics data analysis. Knowledge of advanced biostatistical methods, including
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: “Development of participatory models based on the integration of qualitative and quantitative spatially-referenced data for the co-design and evaluation of nature-based solutions.” Where to apply Website https
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of participatory models based on the integration of qualitative and quantitative spatially-referenced data for the co-design and evaluation of nature-based solutions.” Where to apply Website https
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integration of advanced methodologies for high-resolution meteorological and climate analysis within the RIMU-CLIMA project. In particular, the candidate will carry out activities concerning the integration