About the Project
Background:
The University of Glasgow (UofG) is home to world-leading research in the fields of imaging and computing science. UofG is also home to the UK Hub for Quantum Imaging Technologies, QuantIC (https://quantic.ac.uk/) who are funding this PhD research project. QuantIC is the UK Quantum Technology Hub in Quantum Enhanced Imaging set up to facilitate collaborations between academia and industry to revolutionise imaging across industrial, scientific and consumer markets. Our vision is to pioneer a family of multidimensional cameras operating across a range of wavelengths, timescales, length-scales, creating a new industrial landscape for imaging systems and their applications in the UK.
At the UofG we are leading the development and implementation of the new generation of machine learning techniques. By joining our team you will be part of a unique, world-leading and international research team, with training in cutting edge research techniques involving computing science (including Artificial Intelligence, Machine Learning (ML), data compression), optics and photonics (holography, laser optics, optical communications), and biomedical imaging.
The project:
ML and deep learning (DL) algorithms are nowadays used in a wide variety of different scenarios such as autonomous vehicles, healthcare technologies, and computer vision. However, these algorithms require largescale data processing and an increasingly demand for computational resources. The main consequence is the big amount of energy resources used by ML and DL algorithms, which, together with the limitations brought by Moore’s law for electronic computing -where the scale of an electronic transistor is already approaching its physical limit- encourages the community to look for energy-efficient scalable alternatives.
With this project you will investigate new routes for scalable and energy efficient ML based on optical computing. Optical computing offers low power consumption, processing at the speed of light, and high-throughput capability, which is a basic requirement for high-performance computing. During the project, you will develop new physics-informed ML algorithms and you will demonstrate new routes for their application via hardware, by means of optoelectronic elements.
This ground-breaking approach will help you to design intelligent optical systems performing data-processing and image-processing tasks directly on the hardware at the speed of light.
Fully funded studentships are available at the UK/EU rate. Applicants must have or expect to obtain a first-class degree (2.1 or equivalent) in an appropriate discipline in of science and engineering, this including: computing science, physics, maths, electrical engineering, or other relevant disciplines.
UofG places equality, diversity and inclusion at the heart of its activities, offering part-time studentships, funding to support applications from under-represented backgrounds, childcare support for conference attendance, flexible working for carers as well as prompting a work-life balance.
How to Apply: Please refer to the following website for details on how to apply:
https://www.gla.ac.uk/postgraduate/research/computing/.
You will be required to submit a cover letter, CV, the name of two references and your transcript/degree certificate.
If you have any questions or require further information please email [Email Address Removed]
Funding Notes
Funding is available to cover tuition fees for UK students for 3.5 years, as well as paying a stipend at the Research Council rate (estimated £15,245 for Session 2020-21).
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