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Machine and deep learning for improving photoacoustic imaging for CAR T-cell cancer therapy

   Department of Electrical and Electronic Engineering

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  Dr L.M Florescu, Dr J Bamber, Dr Aoife Ivory  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

This EPSRC iCASE funded project builds on an existing collaboration between the University of Surrey (UoS), the Institute of Cancer Research (ICR) and the National Physical Laboratory (NPL), to develop photoacoustic imaging using artificial intelligence techniques to assist the optimisation of CAR (chimeric antigen receptor) T-cell cancer therapy. This is an emerging treatment technique, approved for patients in 2018 and expected to enable major advancements in personalised cancer medicine.

The project will develop the use of photoacoustic imaging for determining the biodistribution of the CAR-T cells in vivo. Photoacoustic imaging is a powerful biomedical imaging method which employs an ultrasound scanner in combination with a pulsed laser to create high-resolution 3D images of optical absorption spectra and temporal switching characteristics of molecules in tissues and cells. The project objectives involve the application of machine and deep learning to use combinations of spectral and temporal photoacoustic signatures to recognise CAR T cells against background tissue and to quantify CAR-T cell numbers. Methods will be validated against photoacoustic microscopy of cells in tissue-mimicking phantoms and in vivo after tumour or tissue sectioning. Opportunities will be available, given time and interest, to explore dynamic quantification of CAR-T cell numbers as they penetrate tumours.

The student will be based at the UoS in the Centre for Vision, Speech, and Signal Processing (CVSSP), and some time (about three months) will be spent at the ICR and NPL for data acquisition. Training on photoacoustic imaging will be provided.

CVSSP is an International Centre of Excellence in audio-visual signal processing, computer vision and machine learning, advancing scientific and practical application of AI and machine perception. ICR was ranked second, of all UK higher education institutions, in the Research Excellence Framework and is one of the world's most influential cancer research institutes. NPL is one of the most extensive government laboratories in the UK and has a prestigious reputation for setting physical standards for British industry.

The deadline is open until filled but not later than 22 November 2022.

Project supervisors: Dr. Lucia Florescu (UoS), Prof. Jeff Bamber (ICR) and Dr.Aoife Ivory (NPL).

Entry requirements 

Open to any UK or international candidates. Starting in January 2023. An April 2023 starting date is also possible.

You will need to meet the minimum entry requirements for our PhD programme.

All applicants should have (or expect to obtain) a first-class degree in a numerate discipline (mathematics, science or engineering) or MSc with Distinction (or 70% average) and a strong interest in pursuing research in this field. Additional experience which is relevant to the area of research is also advantageous, especially a demonstrated capability in machine/deep learning or interest in convergence research that spans the physical and engineering sciences.

International applicants: IELTS 6.5 or above (or equivalent) with no sub-test of less than 6 

How to apply 

Applications should be submitted via the Vision, Speech and Signal Processing PhD programme page. In place of a research proposal you should upload a document stating the title of the project that you wish to apply for and the name of the relevant supervisor.

Funding Notes

Stipend £ 19,000 pa; covered tuition fees for all years; £5,595 pa for training and consumables.

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