-
microorganisms, and developing of spectral collection and analysis protocols that will allow this biochemical data to be effectively used to support optical microscopy-based deep-learning algorithms for species
-
for generalization in data-scarce situations, and graph neural networks to model relational and topological structures. Other methodological directions include development of customized loss functions for spatio
-
forests and marine environment and pest surveillance in aquafarming. Our group will comprise a handful of PhD candidates, and several researchers and MSc students and also a broad interdisciplinary network
-
development of purification protocols to achieve ultra-high homogeneity. Practical experience with, and knowledge of, spectroscopic and isotope-based techniques to characterize and monitor protein self-assembly
-
tomography and mechanical testing. Experience with multidisciplinary environments and collaborative research projects. International networks and experience. Consideration will also be given to how