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Life Science (DDLS), coordinated by SciLifeLab, aims to recruit and train the next-generation of data-driven life scientists and to create globally leading computational and data science capabilities in
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to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), coordinated by SciLifeLab, aims to recruit and train the next-generation of data
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. Additional qualifications Experience from providing support in image analysis to other researchers is meriting. Especially meriting is proficiency in using and developing algorithms and analysis pipelines
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the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms, scientific software
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comprehensive analysis of complex imaging mass spectrometry datasets (e.g., MALDI-MSI, DESI-MSI) using established computational frameworks Develop and implement novel algorithms and visual analytics for spatial
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develop new algorithms where needed: this may include the incorporation of genomic or other omic data 2) An important second part of the post is helping to automate components of interpretation and
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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Department of Clinical Microbiology The Dwibedi research group at the Department of Clinical Microbiology and the Laboratory for Molecular Infection Medicine Sweden (MIMS; https://www.mims.umu.se
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applications. Documenting experiments and method development for project tracking and publications; being updated with current with relevant technologies and scientific literature; and participating in
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to handle the massive amounts of data generated by novel high-throughput scMetaG methods. Here, the PhD student will develop novel bioinformatic methods and tools, which can be used to analyze massive amounts