SFI-funded PhD Studentship at the Digital Enterprise
Research Institute (DERI), NUI Galway
Dynamic Graph and Network Analysis
The SFI-funded Clique Strategic Research Cluster at the Digital Enterprise Research Institute (http://www.deri.ie), NUI Galway (http://www.nuigalway.ie) invites applications for a funded PhD Studentship in Dynamic Network Analysis.
Clique (http://www.cliquecluster.org) is a funded research cluster of six academic principal investigators, industry collaborators and collaborating academics – based at the DERI, NUI Galway and University College Dublin. The research cluster addresses the development of analytical, modelling and visualisation techniques for the analysis of large scale, dynamic graph and network data. In particular, we are interested in the principles underlying the evolution and dynamics of large computer-mediated social networks, device-mediated communication networks and biological networks. Some areas we are interested in include:
- Analysing how communities (highly connected sub-graphs) in these networks form and evolve with time. Analysing cross-community dynamics
- Analysing how information and innovation diffuses and formulating models to describe the observed diffusion behaviour;
- Analysing churn in online communities and mobile call networks.
The successful candidate will analyse how particular properties of the networks change, and use network changes to detect abnormal events or to predict how information diffusion is enhanced or hampered. The successful candidate should have a bachelor’s degree in computer science, maths, science or engineering, and have the pre-requisites for PhD studies at NUI Galway (http://www.nuigalway.ie). The PhD studentship covers academic fees and includes a generous stipend for a four year period. In addition, desired, though not necessary, requirements are:
- Familiarity with basic graph theory (e.g., finding connected components, shortest paths);
- Familiarity with modelling and simulation
- Familiarity with social network analysis;
- Familiarity with dynamic data analysis (e.g., data streaming algorithms, incremental algorithms);
- Familiarity with text mining, feature extraction and machine learning
- Masters or equivalent degree in graph analysis, modelling or social network analysis.
The successful candidate will work with the PI Dr. Conor Hayes and Dr. Jeffrey Chan as part of the Clique Research Cluster at DERI, NUI Galway. Interested applicants should send an application with the subject header CLIQUE_PhD_09 to conor.hayes@deri.org. The application should contain a CV, a one page statement explaining how the candidate's background is compatible with the aims of the Clique Research Cluster and a list of references. Closing date: September 15th, 2009.
