Feature detection and analysis in scientific data
- Self-funded PhD students only
- Number of awards: 1
- Deadline: Ongoing
- Supervisors: Contact Dr Hamish Carr to discuss this project further informally.
As data sizes scale, feature detection & analysis are increasingly important aspects of scientific computation. However, these approaches are typically developed separately, with little or no interchange between topological methods, machine learning and other forms of analysis. The goal of this PhD would be to analyse the sets of approaches to this task, establish ontologies, articulate the space of possible feature detection methods, and deliver and implement innovative new and/or hybrid feature detection methods.
You must have achieved a bachelor degree with a 2:1 (hons), or equivalent, or a good performance in a Masters level course in a relevant subject. We also recognise relevant industrial and academic experience.
How to apply
Formal applications for research degree study should be made online through the university's website.
If you require any further information please contact the Graduate School Office
e: firstname.lastname@example.org, t: +44 (0)113 343 8000.