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causal inference, integration of heterogeneous data sources, uncertainty quantification Work with a wide range of data types, for example dietary records, biomarkers, omics data, registry data, and sensor
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chromatographic techniques. Integration and synthesis of previous data with newly collected data on fatty acids, cyanotoxins, and stable isotopes. Application of Bayesian mixing models to investigate consumer diets
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. This four-year doctoral project will investigate biotic risks associated with birch and builds on research initiated during the first phase of Trees For Me. It combines two connected research tracks: damage
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science with a focus on bioinformatics. We offer an international, stimulating, and collaborative research environment where your scientific career development is promoted. The project aims to track strain