Ireland : PhD Studentship in Dynamic Network Analysis, Mining and Modelling

The Digital Enterprise Research Institute (DERI) at the National University of Ireland Galway is seeking applications for a funded PhD studentship in Dynamic Network Analysis, Mining and Modelling.

The successful candidate will join the Clique Strategic Research Cluster in DERI at NUI Galway. Clique is a Science Foundation Ireland funded research cluster addressing the development of analytical, modelling and visualisation techniques for large scale, dynamic graphs and networks. The cluster is distributed between DERI and University College Dublin, and has industry partners such as IBM. The DERI group conducts fundamental algorithmic work as well as investigating and modelling the principles underlying the evolution and interactions in large social, communication and collaborative networks. Areas of interest include but are not limited to:

Analysing user roles in social networks and designing efficient algorithms to find these [1];

Analysing and modelling the interactions between online communities [2];

Formulating predictive models for information diffusion in social and collaborative networks;

Designing efficient graph algorithms to find evolving communities with correlated change behaviour [3];

Designing scalable, distributed, real-time algorithms to tackle problems in massive dynamic graph datasets;

The successful candidate should have at least a bachelor's degree in computer science, maths, science or engineering, and have the pre-requisites for PhD studies at NUI Galway. The PhD studentship covers academic fees, a generous monthly stipend and a research travel allowance for a three year period.

In addition, the following criteria are desirable but not necessary:

 

• Familiarity with graph algorithms and theory (e.g., finding connected components efficiently);
• Familiarity with modelling and simulation;
• Familiarity with social network analysis;
• Familiarity with large-scale, distributed, dynamic data analysis (e.g., data streaming algorithms);
• Familiarity with data mining, feature selection and machine learning, especially graph mining and graph grammars;
• Masters or equivalent degree in a relevant discipline or topic

The successful candidate will work with the DERI Principle Investigator, Dr. Conor Hayes, Dr. Jeffrey Chan and Dr. Marcel Karnstedt in DERI, Galway. There will be extensive opportunities for collaboration with other Clique researchers and with other research groups and projects in DERI. The application must contain the following: a CV, a one page statement explaining the candidate's interest in and compatibility with the objectives of the position and a list of referees. Applications that do not follow this format will not be considered. 

References:

[1] Jeffrey Chan and Conor Hayes, "Decomposing Discussion Forums using User Roles", in Proceedings of 2nd Web Science Conference 2010, USA, 2010.
[2] Marcel Karnstedt and Conor Hayes, "Towards Cross-Community Effects in Scientific Communities", in Knowledge Discovery, Data Mining and Machine Learning, 2009.
[3] Jeffrey Chan, James Bailey and Christopher Leckie, "Discovering correlated spatio-temporal changes in evolving graphs", in Knowledge and Information Systems, 16(1), 2008.

 

Please give the reference of CareerSetup in your application when applying for this opportunity! 

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