In the last decade, nanophotonics and nanoplasmonics have become well-established research fields. They benefit from the recent advances in nanofabrication and optical characterization techniques, as well as the accuracy and predictive value that classical electromagnetics has demonstrated down to the nanoscale. In this context, much attention has been focused on revisiting the antenna concept. The so-called nanoantennas (i.e., plasmonic antennas) are devices that function at optics in a similar way as conventional antennas do for low frequency radiation (e.g., microwaves and radio-frequency). Breaking the diffraction limit of classical optics, these nanometric systems allow for the near-to-far-field coupling (and vice-versa) of optical signals with unprecedented efficiency. This nanoscale control over the propagation and confinement of visible light has already found applications in areas such as spectroscopy, biosensing, photovoltaics, optoelectronics, photodetection and nonlinear optics.

The electromagnetic response of plasmonic nanoantennas depends strongly on their geometrical parameters and material properties. The standard approach for their design and modelling based on full-wave simulation and numerical optimization is computationally expensive. Besides, finding a globally optimized result and perform inverse design is not a trivial task. In this multi-dimensional parameter space problem is judicious to look at machine learning.

The PhD candidate will develop deep neural networks for modelling and designing plasmonic nanoantennas such as the trapezoidal logperiodic, particle-on-mirror and logarithmic spiral. The training data will be collected from electromagnetic simulations of the specific nanoantennas using transformation optics (the technique that made possible invisibility with metamaterials) and supplemented with either open-source code or commercial software available in the research group. Further details of the project will be agreed with the interested candidates to tailor the research on his/her interests.

The research programme will take place in an international and interdisciplinary environment, which will substantially favour collaborative opportunities within the College of Engineering and Physical Sciences, and with other research institutions in the UK and afield.

Funding Details

Applications are sought from highly motivated students graduating with first degree (2:1 or higher) in physics or engineering (and preferably a MSci/MEng degree). Funding is awarded on a competitive basis, depending on the strength of the applicant. The funding is only available to UK or EU nationals with (pre-)settled status, and it will cover tuition fees and provide a stipend for 4 years.