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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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encourage all qualified candidates, regardless of background, to apply! Job description The candidate will work on large-scale data analysis of cancer transcriptomics data (bulk, single cell and spatial), and
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
comprehensive quantitative evidence and understanding of their capacity and cost-effectiveness for carbon sequestration under varying conditions. You will be part of a large international research project focused
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are assessed by the PIs of each project, respectively. For detailed information about every project, click the link. 1. Evolution of Scots pine forests since the last glacial maximum https://www.umu.se/en/ucmr
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systems, or network analysis. Experience with methods for causal inference, or modelling of biological systems is also considered a merit, along with prior work involving large-scale sequencing data such as
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, funded by the prestigious European Research Council (ERC-2022-STG #101077370), seeks to understand receptor-mediated transport across the BBB and develop new strategies to deliver large therapeutics
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, leadership, and data science. Special training for writing successful ERC Starting Grants as a ‘ticket’ to an outstanding academic career. Being part of a thriving academic and social community in Vienna, one
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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
foundation in multiple cryo-EM structures. Here the postdoc will work closely together with a PhD student dedicated to this project. The single molecule data will be obtained by the postdoc at a local state of
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics