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primarily computational, working with long-read, short-read, single-cell and spatial transcriptomic data. The successful candidate will develop reproducible analysis workflows; analyse long-read RNA and DNA
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stock changes towards higher Tier levels according to the IPCC guidelines and contribute to the further development of spatially explicit approaches, models and monitoring tools for land-use categories
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such as perceptual, spatial, temporal, emotional, and event content). By removing the burden of manual scoring, these automated tools make large-scale and longitudinal studies of memory possible, including
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from aquatic sediments represent a major uncertainty in the global carbon cycle. This project seeks to advance our mechanistic understanding of methane gas dynamics across multiple spatial scales by
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data integration, and computational tools that preserve the spatial provenance of molecular and physiological datasets. The cluster hire described in this announcement extends these strengths toward
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field. Expertise in analysis of single cell or spatial sequencing data is required. Experience in analysis of bulk RNA and whole exome sequencing data, and genotyping array data is preferred but not
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the objectives more precise; working on the individual PhD study project with its focus on the methodological contributions as well as on empirical data processing for the case study analysis in collaboration with