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Deep Learning for Inverse Scattering Problems

Applications are invited for our EPSRC funded Doctoral Training Partnership (DTP) PhD studentship for the project “Deep Learning for Inverse Scattering Problems” starting 1 April 2022. Successful applicants will receive an annual stipend (bursary) of £17,609, including inner London weighting, plus payment of their full-time tuition fees for a period of 36-months (3 years).

Applicants must be classified as a home (UK) tuition fee paying student to be eligible for this studentship.

The Project

This exciting research project is focused on inverse scattering. When an incident probing electromagnetic, acoustic or elastic field is launched into a medium that contains an object, that object will disturb the field and scatter it. This disturbance can be detected, and this project will explore the use of Deep Learning to use these detected signals to determine the shape of the object.

Please contact Dr Simon Shaw at simon.shaw@brunel.ac.uk to arrange an informal discussion about the project.



Skills and Experience

You will be required to demonstrate knowledge of elliptic partial differential (e.g. Helmholtz) equations, experience in scientific computing (e.g. Matlab, Python, C/C++), and experience in the configuration and use of off the shelf software. You should be highly motivated, able to work independently as well as in a team and be able to effectively communicate verbally and in writing.

Academic Entry Criteria

You will have or be expected to receive a 1st class or 2:1 honours degree in mathematics or another subject with substantial mathematical content. A postgraduate masters degree is not required but may be an advantage.


How to apply

Please submit the documents below as a single PDF file by email to cedps-pgr-office@brunel.ac.uk by 14:00 on Monday 28 February 2022.

  • Your up-to-date CV;
  • Your personal statement (300 to 500 words) summarising your background, skills and experience. Please state the name of the project supervisor at the top of your personal statement;
  • Your Undergraduate/Postgraduate Masters degree certificate(s) and transcript(s);
  • Your English Language qualification of IELTS 6.5 overall (minimum 6.0 in all sections) or equivalent, if applicable;
  • Contact details for TWO referees, one of whom can be a member of Brunel University academic staff.

Interviews will take place in early/mid-March 2022


Meet the Supervisor(s)

Simon Shaw - Simon Shaw is a reader in the Department of Mathematics in the College of Engineering, Design and Physical Sciences, and belongs to the Applied and Numerical Analysis Research Group. He is also a member of the Structural Integrity theme of our Institute of Materials and Manufacturing, and of the Centre for Assessment of Structures and Materials under Extreme Conditions, and of the Centre for Mathematical and Statistical Modelling. Shaw was initially a craft mechanical engineering apprentice but (due to redundancy) left this to study for a mechanical engineering degree. After graduation he became an engineering designer of desktop dental X Ray processing machines, but later returned to higher education to re-train in computational mathematics. His research interests include computational simulation methods for partial differential Volterra equations and, in this and related fields, he has published over thirty research papers. He is currently involved in an interdisciplinary project that is researching the potential for using computational mathematics as a noninvasive means of screening for coronary artery disease. Personal home page: http://people.brunel.ac.uk/~icsrsss