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levels, from molecular structures and cellular processes to human health and global ecosystems. The successful candidate will be working at the SciLifeLab Data Centre, a central unit within SciLifeLab with
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, bioengineering, or related life sciences) Strong organizational skills and the ability to manage multiple tasks and projects in parallel Hands-on experience with experimental laboratory work (e.g. cell culture
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pangenomics of polyploids Project description This PhD project investigates how whole-genome duplication reshapes genome evolution using comparative pangenomics across multiple natural diploid–polyploid species
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Infrastructure (SBDI) and maintains the Swedish Species Observation System. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes
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at the interface of science, healthcare, and policy making Ability to handle multiple projects at the same time required. Strong national and international professional networks Excellent collaborative and
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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managing user-requested proteomics and other MS-based research projects, including hands-on laboratory work. Operation of the MS instruments, Orbitraps (Thermo Scientific) and tims-TOFs (Bruker) interfaced
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on biological processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic teaching and research environment that is internationally recognised for its excellence in
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interest in quantitative biology Curiosity and motivation in learning multiple -omics approaches Preferred experience includes familiarity with quantitative proteomics or NGS library generation Previous
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Giacomello. Examples of tasks: Design, perform, and optimize experimental workflows for ST, SmT and single-cell multiomics Prepare and process animal and plant tissue samples for spatial and sequencing-based