Modelling dynamic molecular networks from advanced imaging data Modelling dynamic molecular networks from advanced imaging data

The mechanisms regulating biological processes (e.g. cell growth, cell-to-cell communication, pathogen infection, etc) rely on controlled dynamics within protein networks that are of high interest for biomedical research. However, such mechanisms remain elusive because their temporal and spatial scale are too small to be captured by
available techniques. Our group, in the frontier between Cell biology and Bioengineering, develops new methods of fluorescence microscopy that allow the analysis of molecular networks beyond the classical limitations. We combine advanced microscopy (such as super resolution microscopy and cryo-electron tomography) and gene editing to time-resolve protein networks in vivo. We offer a position (for a minimum of 6-months with possibility of funding) for a Master student to contribute, together with experimentalists, to model molecular networks at the ms and nm scale based on advanced imaging data. Some of the methodologies employed include: Single particle tracking, Single molecule localization microscopy, Neural Networks and Bayesian inference. The project will be done in
collaboration with the groups of Carlo Manzo (Universitat de Vic) and Jonas Ries (EMBL, Germany).