Since its inception in 2004 with the support of Science Foundation Ireland, the National Centre for Geocomputation (NCG) has become firmly established as a leading centre for research in the field of Geocomputation, applying computational methods to large spatial data sets from acquisition to analysis, modelling and visualisation. The NCG has is offering three PhD studentships to contribute to the multi-disciplinary SFI-funded Building City Dashboards project, undertaking fundamental and applied research on intelligent, dynamic data querying and mining, prediction and simulation techniques, and interactive visualisations and other media..
PhD student 1
With a background in data science, informatics, statistics or geocomputation, this student will develop new techniques for assessing data quality and veracity and determining how to communicate this to users within the dashboard framework. The student will tackle a number of issues/problems, such as: (i) identification, and correction if necessary, of anomalous data; (ii) ecological fallacies; (iii) data standards; (iv) communication of metadata; (v) calibration issues.
PhD Student 2
This PhD student will work on (i) developing a toolkit for assessing the relative design and statistical merits of existing dashboard tools, (ii) test this toolkit through the evaluation and user testing of different forms of dashboard visualisation across existing city dashboards. The toolkit will provide results that will be used to produce a design guide for city dashboards. The student will have a background in informatics or human-computer interaction.
PhD Student 3
This PhD student will work on assessing geodemographic models and creating a geodemographic classification based on streaming urban data. This will involve investigating dynamic approaches to classification such as partitioning against medoids (PAM) and self-organising maps, as well as the ability to add data from less structured sources such as volunteered geographic information (VGI). A key output will be the designing and building an open geodemographics module that can be adapted for other cities. The student will have a background in statistics, geocomputation or data science, preferably with some coding skills.
