Funded PhD Studentship at the Clique Research Cluster, Unit for Information Mining and Retrieval, Digital Enterprise Research Institute (DERI), NUI Galway

At the Clique Research Cluster (http://www.cliquecluster.org), we are investigating and analysing how very large real-life social networks, biological networks and other networks of interest evolve. Some areas we are interested in include:

    * Analysing how communities in these networks form and change with time;
    * Analysing how information and innovation diffuses and formulating models to describe the observed diffusion behaviour;
    * Analysing churn in online communities and mobile call networks.

We are seeking applications for a PhD candidature in dynamic graph analysis. 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 bachelors degree in computer science, maths, science or engineering, and have the pre-requisites for PhD studies at NUI Galway (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.