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ocean, and an urgent need to inform regulatory bodies about associated environmental risks. The work builds upon methods developed in our previous inter- and transdisciplinary work on shipwreck risk
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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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cytometry, FACS, and qPCR for quantifying infection; as well as statistical analysis. You are also likely to use CRISPR/Cas9 technology, CLIP assay, co-immunoprecipitation, and other biochemical methods
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) analysing the effects of different trade-offs between timber production and biodiversity under the influence of climate change, and 3) developing optimisation models based on heuristic and AI-based methods
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include: -Investigate and develop cloud platform to support elastic and cost-efficient AI operations regarding climate change management. -Investigate and develop methods to support user-centric immersive
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include: -Investigate and develop cloud platform to support elastic and cost-efficient AI operations regarding climate change management. -Investigate and develop methods to support user-centric immersive
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at the same time so special. The originality of the experiments is in the combination of X-ray based scattering and imaging methods to monitor the changes at the particle scale during testing. Research
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combination of different methods such as population genetics, analyses of fungal environmental DNA and soil spore banks in soil to find out about the life histories of ectomycorrhizal fungi in general, and
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use Systems Biology methods to formulate a set of ordinary differential equations describing how genes regulate each other across the different organelles. Another approach is to use Monte Carlo