Postgraduate Vacancies

Please contact me if you are interested in submitting a proposal in a spatial related area to any of the open calls:

Active calls:
This section is updated regularly as new deadlines are announced by funding bodies. This is by no means an exhaustive list. Other national or international funding is acceptable and will find supervision support.

If this type of project interests you, please don't hesitate to contact me for similar opportunities.
Our AIRC team currently has a  funded PhD position vacant in the area of GIS/Spatial Databases.

A machine learning approach to spatial content synthesis from crowd-sourcing platforms (for disaster management)

Project summary:

The recent decade has seen an unprecedented surge in available geo-referenced data. Social media providers, such as twitter (text) or flickr (images), have started to incorporate location into their feeds. This provides an opportunity to harness new sources of spatial information that are cheaper than traditional spatial data sources that typically require specialised hardware and expert users. 

   The biggest challenge for effective exploitation of these new spatial data sources lies in merging spatial information that references the same location but originate from different devices or different communication methods. This project aims to merge all layers of spatially referenced information into one spatial data model.

  One application of such a system is the area of disaster management, where it would take heterogeneous sources and incorporate these in real time in an app for laypeople. We already see smart phones used in crisis situations, such as the current refugee crisis from Syria. Currently, app users read information manually from apps such as twitter and newspapers, and then manually process these individual pieces of information to make a route based decision. A system as envisioned by this project would immediately provide a content merge of all relevant information in order to assist decision making in critical situations.

Candidate Requirements:

  • Background or experience in GIS and/or Spatial Databases;
  • Interest in or previous experience with (spatial) data analytics and machine learning, specifically in relation to text and/or image data or other spatially relevant data sources;
  • Documented proficiency in at least one modern, object-oriented programming language, and APIs (such as twitter) and tools (such as version control);
  • Previous experience with a data driven project is beneficial;
  • Experience with or interest in handling data with a spatial component.
  • Fluency in the English language, see the DIT PhD studies web site for  requirements for language test level requirements if your first language is not English, and any other relevant entry requirements;
  • Willingness to relocate to Dublin, Ireland. This position can be offered as part-time study, however be aware that DIT's PhD programme requires a certain amount of taught modules to be completed regardless of full-time or part-time study;
  • Experience in team work and demonstrated self-motivation and drive;

How to apply:

Send CV and a cover letter, including at least two appropriate references, and any additional information to bianca(dot)phelan(at)dit(dot)ie 

Your cover letter must outline how you fulfil the candidate requirements and provide a 500 word abstract of your background research on this topic.

Please don't hesitate to contact me in relation to this position should you require any additional information.