University of St Andrews

Postgraduate Opportunities


We welcome applications for study towards a research degree from candidates with an excellent academic background. The list of projects below indicates the range of interests of our staff, but you are also welcome to suggest your own project in a related area. In the first instance, please contact the relevant member of academic staff to discuss your ideas.

More details on the application procedure are available here

If you have an enquiry about the application process, please contact Mrs Helen Olaez.

New cartographic principles for movement data

Supervisors: Dr Jed Long and Dr Urska Demsar

Recent technological advances have resulted in numerous applications for studying movement trajectories of people, their vehicles and wildlife. Movement data are now increasingly enriched with contextual information about the object or the environment within which they move. While methods for analysing and visualizing movement trajectories continue to improve, basic cartographic principles for generating movement data maps are lacking. This project will involve the development and testing of new cartographic methods for mapping complex movement datasets in order to effectively relay the information content of movement data and analysis. Specifically, focused will be placed on developing static 2-dimensional maps, whereas currently much emphasis is being placed on interactive visualizations. Students with a keen interest in cartography are highly encouraged to apply, and those with existing skills in GIS and computer programming are especially desirable.

Non-linear visualisation techniques for linking movement to its environmental context

Supervisor: Dr Urška Demšar

Visualising the geometry of GPS trajectories is becoming very common. However, since their geometry and temporal progression already use the two or three display dimensions available for visualisation, visually integrating the additional contextual environmental information into the display becomes very difficult. This project will develop new visualisation techniques based on non-linear deformations of 2D graphics. Paths are often difficult to visualise and analyse because our perceptual system cannot easily dissociate their shape from the data. (e.g. it is difficult to estimate the length of a path when the path has many turns). One possible way to address this is to  “unwrap” trajectories into easier geometries that can be readily understood and visually perceived. For example, roads and rivers can be “straightened”, areas can be non-uniformly condensed or expanded, in a similar way as distorting funfair mirrors do. Such non-linear deformations are well known in computer graphics, but their application in movement visualisation has been limited so far. This project requires a student with a degree in geoinformatics or computer science and interest in information visualisation. Note that computer programming experience is essential (Python, java, and preferably visualisation environments, such as Processing and/or D3.js) and students with limited programming experience should not apply.

Spatial-temporal interactions in wildlife: The role of landscape features

Supervisor: Dr Jed Long

Dr Long is seeking a PhD student who is interested in using GIS and spatial analysis to study spatial-temporal interactions in wildlife using data collected via GPS tracking collars. Of special interest is the study of how landscape features (e.g., habitat, roads, barriers) influence the emergence of interactive behaviour in wildlife, considering both inter- and intra-species interactions. Empirical GPS data will come from collaboration between Dr Long and the Samuel Roberts Noble Foundation, who have extensive GPS tracking data on white-tailed deer in the United States. This project is applicable to any student interested jointly in wildlife conservation and spatial ecology. Students with previous expertise in GIS, spatial analysis, statistics, and/or experience in computer programming (e.g., Python, R) will be highly desirable.