Bayesian computation and machine learning for low-photon imaging

The proposed PhD research project aims to develop new computational imaging methods for low-photon imaging problems, with special attention to quantum-enhanced imaging technology that exploits the quantum nature of light to go far beyond what is possible with classical imaging techniques. We are particularly interested in cutting-edge applications such as high-resolution passive gamma emission tomography for nuclear fuel monitoring, low-photon single-pixel multispectral imaging, and single-photon LIDAR-based imaging. Addressing these difficult computational imaging problems will require developing new imaging methods and algorithms, and we will focus on modern Bayesian statistical approaches that leverage ideas and techniques from machine learning, image processing, high-dimensional computational statistics, optimisation, stochastic numerical methods, and mathematical inverse problems.

The position will be available through the University of Edinburgh. The supervision will be provided jointly by Marcelo Pereyra (School of Mathematical and Computational Sciences of Heriot-Watt University), Yoann Altmann (School of Engineering and Physical Sciences of Heriot-Watt University), and Konstantinos Zygalakis (School of Mathematics of the University of Edinburgh).  They will also benefit from the excellent research environment of the Maxwell Institute for Mathematical Sciences in Edinburgh, which is a unique research collaboration between Heriot-Watt University and the University of Edinburgh, as well as from strong interactions with the Heriot-Watt School of Engineering and Physical Sciences and the broader Edinburgh data science community.

If you have any questions on the project or the application process, please contact- Marcelo Pereyra ([Email Address Removed]) and Kostas Zygalakis ([Email Address Removed]).

Applications are welcome from students with backgrounds in applied mathematics, physics, computer science and electrical engineering. Applications should be submitted via the University of Edinburgh's website here- https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&edition=2021&id=511

Applicants should note their interest in this project when submitting their application. Please indicate Dr Zygalakis as your prospective supervisor and give this project title.