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coordinated analysis of long-term ecological data to understand the drivers and consequences of global change on biodiversity. To unravel how populations, interactions between species in natural communities and
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candidates can start as soon as possible and ideally by early 2026. The overreaching aim of REC is to generate a coordinated analysis of long-term ecological data to understand the drivers and consequences
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. Integrate environmental, spatial, and social data into digital twin models for scenario testing and policy simulation. Adapt co-design methods to local contexts in demonstrator sites (Portugal, Sweden, Italy
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This project explores how mutations in chromatin-modifying genes disrupt early neurodevelopment by systematically profiling in vitro neurons using multimodal single-cell and spatial profiling. By
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emissions due to the large temporal and spatial variations in CH4 emission and its underlying processes. The lack of continuous observations of CH4 turnover hinders our understanding of CH4 emission
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This project aims to identify the spatial genetic and adaptive dynamics of tumour microbiome in colorectal cancer. To do so, we will integrate single-cell genomics, transcriptomics and clinical data
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, developmental biology, genetics, biomedicine, or another appropriate field. Previous experience in confocal imaging and image analysis, scRNA-seq data analysis, or genetically engineered mouse models is