The Building City Dashboards project is currently recruiting for a number of positions – more details can be found below.
- Research fellow 36-42 month contract – Closing date Dec 12th 2016
The Research Fellow will contribute as part of an interdisciplinary team to the SFI-funded Building City Dashboards project, undertaking fundamental and applied research on creating effective city dashboards. The researcher will contribute to one of the four work packages below (applicants should make it clear in their application which of the four work packages they want to be considered for). To be appointed as a Research Fellow a candidate will need a minimum of four years of post-PhD research experience (or commensurate experience working in industry) and will need to demonstrate substantial theoretical and applied knowledge through scholarly publications, successful system implementation, and other forms of dissemination, and an aptitude to assist the PIs with the coordination and implementation of the overall project, and to take an active role in helping to secure additional research funding. They will be expected to work effectively as part of a team, maintain active liaison with stakeholders and collaborators, make a significant contribution to the dissemination of project outputs (incl. workshops, publications, web site, etc.), contribute to the development of PhD students participating in the project. The successful candidate is expected to have relevant Geocomputation, spatial statistics or data science, computer science, visualisation/visual analytics, multimedia production skills required to undertake a particular work package.
- Postdoctoral researcher 36-42 month contract – Closing date Dec 12th 2016
The Postdoctoral Researcher will contribute as part of an interdisciplinary team to the SFI-funded Building City Dashboards project, undertaking fundamental and applied research on creating effective city dashboards. The researcher will contribute to one of the below four work packages (applicants should make it clear in their application which of the four work packages they want to be considered for). The successful applicant will be expected to work effectively as part of a team, maintain active liaison with stakeholders and collaborators, make a significant contribution to the dissemination of project outputs (incl. workshops, publications, web site, etc.), contribute to the development of PhD students participating in the project. The successful candidate is expected to have relevant Geocomputation, spatial statistics or data science, computer science, visualisation/visual analytics, multimedia production skills required to undertake a particular work package.
Work Packages
WP 2.2: Investigating scalar issues in visualisation (36 months)
This task will investigate scalar issues in how data are effectively visualised across different media and to use the resultant information to develop appropriate methods for delivering dashboard content on mobile devices. The method will consist of building and iteratively user testing and developing mobile
apps for the Dublin Dashboard. The outputs will be specific apps for citizens to use, but also a design
guide for app developers producing city-focused apps.
WP 2.3 Examining alternative and multi-modal dashboard platforms (36 months)
This WP will investigate and build new modes of exploring city data, including virtual reality 3D city models, augmented reality, and multi-modal forms such as the projection of data onto architectural models or converting some data into multimedia content.
WP 3.2 / 3.4 Creating and assessing techniques for intelligent, dynamic data querying and mining / Developing prediction modelling and simulation techniques for city dashboards (42 months)
This post will address two work packages. The first will move beyond ‘sift-and-search’ approaches to querying data to create techniques for identifying hard-to-spot patterns in very large databases with a wide range of variables. This will involve providing a visual interface for users who are not experts in statistical modelling to examine and explore such relationships. The second will develop simulation and prediction models that enables ‘what-if’ analysis (e.g., ‘what would happen to traffic if a new road was built here?’ The output will be a user centred open spatial interaction modelling module enabling urban predictions and simulations.
WP 3.3 Developing statistical modelling for city dashboards (36 months)
This WP will consider which inferential and confirmatory statistical methods may be usefully applied to dashboard data and develop an open statistical modelling module that will enable users to perform statistical testing of data within the Dublin Dashboard.