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involve a combination of computational and experimental approaches including mammalian tissue culture, genetic engineering, proteomics and animal infection models. A person who is employed as a PhD student
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screening approaches in which millions of distinct nanostructures are produced as a library, incubated with cancer and control cell lines. Cellular outcome will then be used as a selection marker to identify
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large-scale omics datasets, develop and apply statistical methods and interpretable AI models, and contribute to the identification of biological markers and molecular mechanisms associated with disease
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or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
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applications in different project contexts. This may include data analysis, modelling, literature reviews, and interaction with relevant stakeholders. The results are expected to contribute increased knowledge
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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, interdisciplinary, and highly collaborative environment. Ability to navigate UNIX filesystems from the command line, working in conda environment, installation and implementation of packages from github, batch job
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knowledge-based models and practical guidance that strengthen audit firms’ capabilities in delivering sustainability assurance, support the work of regulatory authorities, and enhance trust in sustainability