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- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen
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health, though expertise in these areas is not required for applicants. The position will involve primary responsibility for data organization and statistical analysis, as well as co-authorship
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; to discover new drugs and biomaterials through: preparation of hard and soft tissue preparation of human and animal samples for biological and imaging analysis studying disease mechanisms. You will process
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other members of the EeMi project working on sedimentology, stratigraphy, inorganic geochemistry, elemental analysis, and other proxies. The position is based in the Department of Geo-energy and Storage
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. A solid publication track record in the relevant field of expertise. Experience with thermal image analysis is an advantage. Experience with hardware such as drones and cameras are an advantage. Good
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upstream regulator of epigenetic and transcriptional reprograming underlying EMT. Nature Communication. Aug 2017. Dynamics and function of distal regulatory elements during neurogenesis and neuroplasticity
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extraction) that can be miniaturized and integrated into portable devices. Perform SERS measurements and data analysis of SERS data (e.g., using machine learning). Develop, test and apply new fiber-based SERS
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microenvironments. To achieve that we use state-of-the-art single-cell RNA-seq, multiome, and spatial transcriptomics data generation combined with computational analysis to establish principles of blood lineage
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genetic analysis, aiming to elucidate the adaptive potential of species in the face of climate change. You will: Conduct ecological fieldwork at research sites in Sweden and Denmark. Collect and analyse
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mathematics, multivariable data analysis, test and validation, and instrumentation. Your Competencies The applicant should have good knowledge of chemicals such as hydrogen, carbon dioxide, methanol. Experience
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ATAC-seq, single-cell RNA-seq, spatial gene expression, and whole-genome sequencing (with long reads) data. The candidate will get the opportunity to explore new analysis methods using deep learning