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We are always looking for talented PhD students and postdocs! Please contact us if you would like to become part of the team! A list of currently available positions can be found below.

High-performance computational modelling of random electromagnetic scattering

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Despite its ubiquity in nature, multiple scattering of light is notoriously difficult to theoretically model. While in principle the scattered field follows exactly from Maxwell’s equations, numerous approximations are generally required to render the solutions tractable. Full finite element based solution of the relevant wave equation offers the greatest rigour, but suffers from limited simulation volumes and large computational costs. Alternatively, methods such as diffusion, Monte Carlo or Greens function calculations adopt a more approximate treatment in turn foregoing physical accuracy.

In previous work we have developed a random matrix based approach to study propagation of polarised light through random media which balances computation time with physical rigour. In this PhD project you will develop the next generation of high-performance modelling tools capable of simulating electromagnetic scattering in complex and disordered media. You will extend our previously developed random matrix model to enable modelling of more realistic optical scenarios with large mode densities, near field components and optical losses. Your work will include parallelising the simulations via GPU implementation, bootstrapping and advanced cubature based techniques. Extensions to describe scattering from more complex scattering environments, such as human tissue, will also be developed.

Please contact Matthew Foreman for further information.

Sensing properties of unconventional whispering gallery modes resonances

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The ability to detect single molecules and precisely monitor their behaviour is critical to understanding key processes in biology such as protein folding, DNA synthesis and membrane transport. Modern biosensing techniques often exploit the advantages offered by optical technologies, namely speed, flexibility and low cost. An important and powerful example is that of a whispering gallery mode (WGM) sensor in which light is confined in a dielectric microstructure and brought to repeatedly interfere with itself. As a result, only specific optical frequencies can be supported and reside within the cavity without suffering large losses. Sensitivity to single bioparticles has been demonstrated by monitoring perturbations to the spectral properties of optical WGMs and hence they represent an indispensable component of next generation high-performance optical biosensing.

In the quest to push the sensitivity limits to enable detection of smaller bioparticles, or facilitate earlier disease detection, we have recently considered advanced WGM sensing platforms, such as hybrid photonic-plasmonic systems and droplet resonators. In this PhD project a number of novel unconventional whispering gallery modes will be studied theoretically and their sensing characteristics established. Analytic techniques to enable quantification of bioparticles, including size, shape and enantiomer characterisation will be established. The ideal candidate has a keen enthusiasm for theoretical optics and an interest in development of new applied methodologies for optical sensing. They would have a first degree in physics, engineering, or mathematics with strong analytical, mathematical and programming skills.

Please contact Matthew Foreman for further information.

Polarisation Imaging in Random Media

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Development of quantitative techniques for measurement and monitoring of biological tissues is vital to improving healthcare and quality of life. Significant effort and resources have thus been invested to improve both the sensitivity and specificity of current bioimaging technology, with optical techniques at the fore. Predominantly, however, current methods are based on measurements of optical intensity or wavelength. Such measurements forego the additional information afforded by study of the degrees of freedom associated with the polarisation of light.

Polarization imaging modalities offer additional contrast mechanisms in biological imaging, such as quantification of collagen density through study of tissue birefringence or diattenuation. Furthermore polarisation measurements can reveal the micro-structure and composition of tissues, e.g. structural differences in elastin can result from burns, photodamage and/or the development of skin cancer. Although non-invasive in-vivo bioimaging methods are highly sought after, they can frequently be impeded by the need to image through relatively thick layers of highly scattering tissue, such as skin or breast tissue. Upon transmission of light through tissue the intensity and polarisation structure of the incident wave is modified, primarily due to scattering from e.g. cell nuclei or mitochondria, but also due to spatially varying birefringence and diattenuation from e.g. collagen networks. This PhD project will focus on theoretically establishing novel techniques for polarisation imaging through disordered media for example by exploiting polarisation correlations and higher order statistical properties, machine learning and informatics. The student will help build analytic models to describe evolution of polarised light in random media and analyse a number of key problems including control of local polarisation in deep tissue, localisation and orientational measurements of buried fluorescent molecules and determination of structural properties of scattering tissues. The ideal candidate has a keen enthusiasm for theoretical optics and an interest in development of new applied methodologies for bioimaging. They would have a first degree in physics, engineering, or mathematics with strong analytical, mathematical and programming skills.

Please contact Matthew Foreman for further information.

Complex Photonic Network Ensembles for Sensing Applications

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Complex and random nanophotonic networks, formed for example by a web of interconnected optical waveguides, are an emerging optical technology offering a unique and novel approach to light transport, lasing, data processing and optical control. Intrinsically, light propagating in an optical network, or graph, undergoes multiple scattering, which can lead to a diverse range of phenomona such as Anderson localisation, loop resonances and long range correlations. Moreover, optical modes formed by recurrent scattering and interference, are highly sensitive to network topology, connectivity, scattering node properties and the balance of optical losses and gain. In our group we have recently shown that multiple scattering in a quasi-two dimensional optical systems, can be leveraged to significantly enhance the sensitivity of optical single molecule biosensors when these cooperative and localisation effects are appropriately engineered. Complex photonic networks therefore represent a promising, yet unexplored, platform for sensing which will be explored in this PhD project.

During the course of this project, the student will develop rigorous simulation models for light propagation in random and complex photonic networks and study the statistical properties of different network ensembles. Enhancements of light-matter interactions will be theoretically investigated and the use of spectral transmission properties for network fingerprinting established. Physically constrained and machine learning based algorithms will be developed for sensogram analysis, system optimisation and network design. The ideal candidate has a keen enthusiasm for theoretical optics and an interest in development of new applied methodologies for optical sensing. They would have a first degree in physics, engineering, or mathematics with strong analytical, mathematical and programming skills.

Please contact Matthew Foreman for further information.