Supervisor: Dr Vincenzo Nicosia
Project description:
A vast class of complex systems in different domains, from biology to sociology, are naturally embedded in space, so that the relations among their constituent are morphed and shaped by the existence of spatial constraints which introduce a cost/benefit value to each link. Many of those spatial complex systems can be modelled as networks, where each node represents an entity and edges signify the existence of a relation between two entities, and those nodes often have metadata associated, in the form of labels or colours. Notable examples span a variety of domains and scales, from plant tissues (where cells are nodes, the relation is physical adjacency, and node labels are specific cell functions) up to animal societies, where individuals are represented by nodes, links indicate predation/collaboration/competition, and node colours indicate specific role).
The main focus of this project is the proposal of analytical and numerical models of the formation and evolution of meaningful patterns in spatial networks with coloured nodes. The student will work on generative models that are able to recreate spatial networks with clusters and motifs similar to those observed in real-world data sets, with the aim of identifying the . The models will be validated across a range of real-world data set, made available through ongoing collaborations with research groups in plant biology (Prof. Bassel, Warwick), urban studies (Prof. Marc Barthelemy, CEA), and brain networks (Prof. Goni, Purdue).
The student is expected to posses a good balance of analytical and computational skills, with a preferable background in mathematics, physics, computer science, and a propensity towards working in an highly interdisciplinary and very dynamic research environment.
Further information:
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Fees and funding