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of breast and lung cancer cells Use of high-resolution methods such as large-scale sequencing Multiplex IHC and image analysis Data analysis and programming in R Independent interpretation of results and
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, Sanger sequencing and phylogenetic analysis of viral sequence data Previous experience of research (e.g. research preparatory courses/ experience of work in research project or similar) Working with
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of manufacturing process parameters. Rather than running expensive physical experiments at random, the goal is to design experiment sequences that maximally reduce uncertainty about which process conditions lead to
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methods such as large-scale sequencing Multiplex IHC and image analysis Data analysis and programming in R Independent interpretation of results and acquisition of new knowledge and methods Active
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of complex single-cell data. The software is designed from the ground up for a new type of data (single-cell whole-genome sequencing/metagenomics), and how to best analyze the data is an open research problem
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student who will work experimentally with microbial and human DNA sequencing, including associated analyses using standard bioinformatics methods. The project will also involve statistical analysis in R
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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of microbial communities using 16S rRNA gene sequencing, followed by bioinformatic analysis. It further includes applying hierarchical and mixed‑effects models and integrating microbiome data with environmental
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gastric cancer tissue and malignant ascites using single-cell RNA sequencing and computational mapping to NK-cell reference atlases. Engineering TME-resilient NK cells through precise genetic editing of key
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and other key actors, the project explores which governance models and policy instruments are most effective in achieving multiple objectives. The goal is to generate new knowledge about how forest