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and bioinformatic analysis of gene expression data in different types of tissues: mice, humans and plants. This work will include analysis of data generated with the latest Spatial Transcriptomics and
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mandatory requirement for English equivalent to English B/6. Selection In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process
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of large-scale multi-omics cancer data. Proven experience in development of bioinformatics tools and software packages. In-depth knowledge in NGS data processing from whole genome sequencing and RNA-seq
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) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global
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sinks, recent research has shown that they can also emit methane, nitrous oxide, and underexplored VOCs. Microbial activity is key to these emissions, but we need to understand how different processes
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. The candidate will combine experimental and computational approaches. The project will start with bioinformatics-driven analysis, followed by integration of data generated from experimental models. Over time, the
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. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
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relevant to the subject area. In the appointment process, special attention will be given to research skills. We are looking for candidates with wet-lab expertise in RNA biology and next-generation
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of organisms, and how these processes respond to environmental changes. Recent advancements in plant and animal physiology have been accelerated by the use of novel single-cell and tissue analysis techniques
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. The data-driven life science initiative Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular