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data. Statistical analysis using R and/or Python. Reproducible computational workflows. Scientific writing and publication. Microbiome research and host-associated microbial communities. The ideal
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tracking analysis (NTA), NanoFlow cytometry, and advanced imaging techniques, as well as bioinformatic analysis of small RNAs and transcriptomic data. You will collaborate closely with partners working
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-based products. The candidate will be involved in data collection, quantitative data analysis, interpretation of findings, preparation of deliverables, writing of academic articles and ongoing development
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and methodological analysis of how landscape change influenced the historical development of environmental anthropology in the Kalahari and should be prepared to work in a collaborative research team
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evolutionary genomics and population genetics, with demonstrated experience applying evolutionary-genomic methods to whole-genome data. Extensive hands-on experience with bioinformatic analysis of whole-genome
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and fungal spores. The geographical focus is on both the urban environment and agricultural areas in Denmark • You will be contributing to the dynamical integration of near real-time data into WRF
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/or eating disorders, data analysis and statistical modeling. Prior experience working with Danish registers is an advantage. As a person, the ideal candidate will have good interpersonal skills, will
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to research on food systems that results in relevant and positive societal impact (for more information see www.mapp.au.dk ). The research project CIRCULARIS – Circularity Indicators and Resource Circularity
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Computational Sciences or similar. You have strong expertise on analyses of biology-related large datasets. Expertise in single-cell and spatial data analysis, spatial statistics and annotation is an advantage
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to experimentally derived disorder models and data from methods such as total scattering/pair distribution function analysis, diffuse scattering, diffraction, solid-state NMR and electron microscopy. Work closely