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PhD Studentship: Machine Learning Tools for X-Ray Imaging

School of Engineering

Location:  Highfield Campus
Closing Date:  Friday 09 November 2018
Reference:  892317KR

Project Reference: ISVR-SPCG-373

X-ray imaging allows us to look inside objects. This is useful in many medical and industrial applications.

This PhD project will look at x-ray imaging applications where an object is made up of different materials and where these different materials vary widely in their x-ray absorption. In this setting, parts of the object will often be opaque to x-ray transmission whilst other parts do not offer significant x-ray contrast, which means that standard tomographic techniques will not be applicable.

You will address this challenge using advanced machine learning and image processing tools. This project will be largely computational, requiring you to develop new tomographic reconstruction algorithms and to implement these to run on the latest graphical processing units for efficient computation. You will also have the opportunity to collect x-ray data in one of our industrial x-ray scanners and to use this data to evaluate the performance of your new methods.

You will join a multidisciplinary team of PhD students and Postdoctoral Researchers that work on a range of issues in x-ray tomographic reconstruction. You will have access to the University of Southampton’s world leading x-ray imaging centre and supercomputing facilities. There is also the opportunity to spent part of your second and third year with our partner institution in Lyon, France.

This project is funded by the joint PhD program of the UK’s Defense Science and Technology Laboratory and the French Direction Générale de l’Armement and is in collaboration with the UK’s Atomic Weapon Establishment (AWE). This work is also linked to a large UK research council funded project that will use similar techniques for the inspection of components in the aerospace industry. Due to restrictions by the funding body, this position is only open to UK and French nationals.

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

Funding and Eligibility

Due to restrictions by the funding body, this position is only open to UK and French nationals. The studentship covers UK/EU tuition fees and provides an annual tax-free stipend at the standard EPSRC rate, which is £14,777 for 2018/19.

How to Apply

Click here to apply and select the programme - PhD in Engineering and the Environment. Please enter the title of the PhD Studentship in the application form.

The closing date for this job opportunity has now passed, and applications are no longer being accepted for this position

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