- Value: This project is open to self-funded students and is eligible for funding from the
School of Mathematics Scholarships,
EPSRC Doctoral Training Partnerships, and
Leeds Doctoral Scholarships.
All successful UK/EU and international applicants will be considered for funding, in an open competition across the School of Mathematics. To be considered for this funding, it is recommended to apply no later than 31 March 2018 for funding to start in October 2018. However, earlier applications are welcome, and will be considered on an ongoing basis.
- Number of awards: 1
- Deadline: Ongoing
Many data sets are collected with an irregular spatial and/or temporal structure, and these data need careful analysis. One approach is to use a lifting scheme which analyses the data one point at a time, looking for similarities and differences between that data point and its neighbours. (Here, neighbours could be close by in space, time, or both.)
This information is recorded as as set of lifting coefficients, one for each data point. The lifting scheme is one of a type of approach referred to as a multiscale method. Another multiscale approach is to analyse the data using wavelets, and indeed the lifting scheme grew out of work on wavelets. Both use the concept of "resolution levels" -- roughly speaking, activity which is captured at one level is acting at about twice the frequency of activity at the next level.
While resolution levels are intrinsic to wavelet methods, they are an artificial construct in lifting. So far, there has been relatively little investigation of what happens if you move away from this artificial structure and allow each lifting coefficient to exist somewhere on a whole continuum of resolution rather than at discrete levels.
This project will investigate the benefits of using a continuous resolution continuum over discrete resolution levels in 1 dimension (eg transects), 2 dimensions (spatial data) and 3 dimensions (spatio-temporal data). if time permits, we would also plan on looking at the relative merits of treating spatio-temporal data in a truly 3D way as compared to taking a 2D "slice" of the data at each time point.
There are many possible applications of these methods, including climatology, disease mapping, seismology, and tomography. Which are studied in depth will depend on the interests of the PhD student.
Applications are invited from candidates with or expecting a minimum of a UK upper second class honours degree (2:1), and/or a Master's degree in a relevant engineering or science degree such as (but not limited to) mathematics and statistics.
How to apply
Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section that the PhD you wish to be considered for is the 'Multiscale spatio-temporal modelling’ as well as Dr Stuart Barber as your proposed supervisor.
If English is not your first language, you must provide evidence that you meet the University’s minimum English Language requirements.
We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.