406 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "The University of Gothenburg" research jobs at Nature Careers
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analysis) Data collection, documentation, and basic data analysis Contribution to reporting, presentations, and potentially scientific publications Supporting collaboration within the research group and with
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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departments. Contact information For further information, please contact: Dr., Peter Zeller, peter.zeller@mbg.au.dk Deadline Applications must be received no later than 23 February 2026. Application procedure
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transcriptomic data. • Detect and interpret structural variation from Nanopore/PacBio sequencing. • Build scalable, reproducible pipelines for large genome collections and public databases. • Collaborate closely
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deformation and damage model for high-temperature fatigue Performing FE simulations of damage development at the microstructure and component levels Exchanging information and presenting the results with and to
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as of that date be with a department Contact information For further information, please contact: Prof. Alfred Spormann, aspormann@inano.au.dk. Application procedure Short-listing is used. This means
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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technologies. Responsibilities: Design and optimize genome editing strategies for custom cell lines Develop and troubleshoot CRISPR-based approaches Analyze and interpret experimental data; present findings
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Ph.D.) in biology, biochemistry, biotechnology or a related field and have published previously in peer-reviewed journals. Knowledge in single-cell RNA-seq, laboratory automation and data analysis, and
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Integration of lifestyle, metabolic, and genomic data to refine early detection and prevention strategies Disparities research and risk modeling to optimize equitable deployment of new cancer screening