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Applications are invited for a Postdoctoral Research Fellow in experimental quantum and optical technology.
The post is available initially for a fixed-term duration of 1 year, with the possibility of extension for an additional 1 year.
Project 1: Superresolution imaging via linear optics in the far-field regime
Rayleigh's criterion defines the minimum resolvable distance between two incoherent point sources as the diffraction-limited spot size. Enhancing the resolution beyond this limit has been a crucial outstanding problem for many years. A number of solutions have been realized; however, all of them so far relied either on near-field or nonlinear-optical probing, which makes them invasive, expensive and not universally applicable. It would therefore be desirable to find an imaging technique that is both linear-optical and operational in the far-field regime. A recent theoretical breakthrough demonstrated that “Rayleigh’s curse” can be resolved by coherent detection the image in certain transverse electromagnetic modes, rather than implementing the traditional imaging procedure, which consists in measuring the incoherent intensity distribution over the image plane. To date, there exist proof-of-principle experimental results demonstrating the plausibility of this approach. The objective of the project is to test this approach in a variety of settings that are relevant for practical application, evaluate its advantages and limitations. If successful, it will result in a revolutionary imaging technology with a potential to change the faces of all fields of science and technology that involve optical imaging, including astronomy, biology, medicine and nanotechnology, as well as optomechanical industry.
Project 2: Optical neural networks
Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass humans in playing board and computer games, driving cars, recognizing images, reading and comprehension. It is probably fair to say that a modern machine will perform better than a human in any environment it has complete knowledge of. These developments however impose growing demand on our computing capabilities, including both the size of neural networks and the processing rate. This is particularly concerning in view of the decline of Moore’s law.
The project is to implement artificial neural networks using optics rather than electronics. The training of neural network consists of linear operations (matrix multiplication) combined with nonlinear activation functions applied to individual units. Both these operations can be implemented optically using lenses, spatial light modulators and nonlinear optical techniques such as saturable absorption. However, one crucial element of the training procedure - so-called backpropagation - has so far remained elusive. Our group has developed an idea to overcome this obstacle and implement pure optical backpropagation in a neural network, thereby enabling the training that is practically electronics-free. We confirmed the viability of this approach by simulation. Our next goal is to set up an experiment and test the method in a practical setting.
Applicants should hold a PhD or equivalent, or be near completion thereof, in physics or a related field.
Candidates are expected to possess a superb past research/publication record, excellent understanding of experimental optics and quantum physics as well as strong scientific writing skills.
The post-holder will have the opportunity to teach.
Only applications received before midday (UK time) 28 February 2021 can be considered. You will be required to upload a statement of research interests, CV and details of two referees as part of your online application.
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