PhD Studentship: Advanced optimisation algorithms for tomographic image reconstruction

United Kingdom
Dec 14, 2015
Dec 01, 2016
Organization Type
University and College
Full Time

PhD Studentship: Advanced optimisation algorithms for tomographic image reconstruction

Signal Processing & Control Research Group

Location:  Highfield Campus
Closing Date:   Thursday 01 December 2016
Reference:  664315KR

Project Reference: ISVR-SPCG-118

Project Themes:  Mechatronics, signal processing and control, Computational Engineering, Materials & Surface Engineering

Joining Dr Blumensath and his team at the University of Southampton’s µ-VIS volumetric imaging centre  (, you will be working on the development of advanced optimisation algorithms to solve advanced x-ray imaging problems. X-ray computed tomography can take volumetric images of the inside of a patient or an object, however, modern applications require the reconstruction of images from limited measurements and this increasingly leads to complex, large scale optimisation problems that have to be solved efficiently. The algorithms you will be developing in this project will be based on the latest developments in the field of compressed sensing, numerical optimisation and inverse problems. You will have access to high end computing facilities, including the University’s supercomputer cluster and dedicated high specification volumetric image processing facilities. You will be hosted in the Faculty of Engineering’s Signal Processing and Control group and work closely with experts from the µ-VIS x-ray imaging lab. µ-VIS is one of the world’s leading x-ray facilities. It has 6 complementary CT systems and lab members have extensive experience using synchrotron facilities. The ideal candidate has an interest in image processing and applied mathematics and good programming skills.

If you wish to discuss any details of the project informally, please contact Thomas Blumensath, Signal Processing and Control research group, Email: Tel: +44 (0) 2380 59 3224.

To apply please use the following link and select Faculty of Engineering and the Environment.