14 October 2022
Computer Science: Fully funded EPSRC DTP PhD scholarship: Visualisation of temporal networks through interactions with the space-time cube
Dynamic data sets where each element of the data has its own individual timestamp has become more prevalent. Algorithms for drawing temporal networks within the space-time cube (2D + t) have been devised to allow dynamic graphs to be visualised in an event-based way. However, three-dimensional representations of non-spatial information are difficult to navigate. Therefore, interactive systems are necessary to fully understand the graph structure and how it evolves over time.
The student will investigate perceptually effective ways for dividing and visualising the space-time cube. The project will start by visualising the contents of this space-time cube with an embedded network drawn with an event-based dynamic graph drawing algorithm. The visualisation methods in this case will focus on visualising the already present structure within the drawing which takes into account both spatial position and time simultaneously. Then, we will explore methods that are able to draw the dynamic graph on demand in the space time cube steered by the user.
Candidates must normally hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).
English Language requirements: If applicable – IELTS 6.5 overall (with no individual component below 6.0) or Swansea recognised equivalent.
This scholarship is open to candidates of any nationality. Please note, there is an International quota for all UKRI funded scholarships. If the quota has been reached by the closing date, please note you may no longer be eligible for this scholarship.
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This scholarship covers the full cost of tuition fees and an annual stipend of £16,062.
Additional research expenses will also be available.
Please visit the website for more information