The partners bring a wide variety of statistical applied mathematics driven-challenges which, through facilitated group work and creation of small, mixed-expertise teams, will be re-formulated into large mathematical questions that can be taken forward as PhD projects. These include:
- Using measured light intensity and “inverting” it to reconstruct images. Can this be achieved when the scattered signal is not wavelength resolved? How to deconvolve the signal based on a spectral shaping of the probe light?
- Informing the experimental design based on mathematical limitations. What sort of experimental set-up (such as acquisition parameters, functional form of spectral shaping) would be optimal for specific image processing tasks?
- Is it possible to use hybrid techniques, such as combining coherent diffraction imaging with lateral shearing interferometry or Fourier transform spectroscopy?
- Handling large multi-dimensional data-sets combined with efficient and robust computational algorithms.
- Modelling of electricity grid dynamics accounting for short-term and long-term characteristics of wind and tidal power generation.
- Improved modelling of wind turbine dynamics and fatigue to allow more sustainable design, construction and control of wind turbine blades.
- Quantifying uncertainty in renewable energies and optimisation of placement of generators, including tidal and wave energy generation.