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dysfunction in Alpers’ syndrome. The student will receive training in a wide range of techniques including tissue culture, immunofluorescence and quantitative microscopy, metabolic assays, and data analysis
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the objectives more precise; working on the individual PhD study project with its focus on the methodological contributions as well as on empirical data processing for the case study analysis in collaboration with
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characterization of deep-water habitats, GIS spatial analysis of species distribution data, and quantification of ecosystem services. Preference will be given to applicants that possess a diverse set of skills and
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helping them in their experiments, acquisition, analysis and interpretation of data. Another requirement would be the ability to write reports, make presentations and contribute to writing the grant
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and data analysis. You will be working at the interface of chemistry and chemical engineering to improve the enrichment process. This will involve investigating different extractants, solvents, and
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
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on: Technical Expertise: Documented skills in Python, Matlab, R, and a strong working knowledge of UNIX environments. Proven familiarity with biological omics data analysis techniques is essential, along with any
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programming skills (in Python, R or similar) and experience with large-scale data analysis using bioinformatic tools and pipelines to analyse and interpret biological data Attributes and Behaviour • Be
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of the Discrete Choice Experiments in Mozambique and South Africa, and the analysis of the ensuing data Develop computational models of health actors’ decisions and responses to regulatory options Collaborate with