-
integrates molecular biology, glycomics, and biochemical analysis to understand influenza attachment and tropism. We are a collaborative group that values complementary expertise and interdisciplinary training.
-
; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting pathogen invasion success and plant
-
assays, such as microelectrode array recordings and (cellular) imaging. In addition, you will investigate if herbal extracts can affect the function and integrity of the protective blood-brain-barrier
-
: molecular and cell-based assays of influenza receptor binding; enzymatic modification or biosynthesis of glycans; biochemical characterisation of virus–glycan interactions. These insights will be integrated
-
, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting
-
’ economic vulnerability.” Your tasks Together with your supervisory team, you will design and conduct novel empirical studies; You will integrate new insights across disciplines, including sociology
-
, resulting in inconsistencies across soil properties and underperformance in data-scarce regions. This PhD project will develop next-generation machine learning methods for geospatial prediction by integrating
-
sociologists collaborate with civic organizations to generate and integrate insights into how connections between individuals, groups, and institutions contribute to new pathways to and forms of social cohesion
-
; biochemical characterisation of virus–glycan interactions. These insights will be integrated to define glycan features that govern influenza attachment and to develop advanced in vitro receptor models