|Funding for:||UK Students, EU Students|
|Funding amount:||£14,777 per annum (RCUK rate for 2018/19)|
|Placed On:||8th August 2018|
|Closes:||7th September 2018|
We are looking for an enthusiastic and talented PhD student to join a multidisciplinary research team to work under the supervision of Dr Lindsay Nicholson in the School of Cellular and Molecular Medicine and Dr Alin Achim in the School of Computer Science, Electrical & Electronic Engineering, and Engineering Maths. They should have some experience in either an engineering or a cellular immunology environment, and a willingness to embrace this multi-disciplinary project.
Uveitis is an important clinical problem and a common cause of preventable blindness. Current measures of disease activity are largely subjective, based on optical coherence tomography (OCT) where low contrast, low resolution and sensor noise are present. We hypothesise that by applying non-linear processing rules, based on sparse-processing methods, we will be able to better correlate images with tissue state.
The study will analyse the eyes of animals with uveitis, where the disease state is known, imaging the retina by photography and OCT. Combining imaging modalities using modern methods of computational imaging will then develop our understanding of how to interpret changes in tissue.
The project will investigate the assessment of disease by devising novel algorithmic approaches to image analysis. The first approach is FUSION, which describes the computer aided superposition of pictures of the same object, obtained in different ways. The second aspect of this project is CLASSIFICATION. This uses machine learning to uncover reproducible patterns that indicate the underlying state of the tissue. The final part of the project will be applying the novel features uncovered by the student to images obtained from patients with uveitis. This project is appropriate for an individual with skills necessary to bridge the gap between computational imaging and its application to difficult medical problems.
Anantrasirichai, N., L.B. Nicholson, J.E. Morgan, I. Erchova, K. Mortlock, R.V. North, J. Albon, and A. Achim. 2014. Adaptive-weighted bilateral filtering and other pre-processing techniques for optical coherence tomography. Computerized Medical Imaging and Graphics 38:526-539.
Lee, R.W.J., L.B. Nicholson, H.N. Sen, C.C. Chan, L. Wei, R.B. Nussenblatt, and A.D. Dick. 2014. Autoimmune and autoinflammatory mechanisms in uveitis. Semin Immunopathol 36:581-594.
Nicholson, Lindsay B. 2016. The immune system. Essays In Biochemistry 60:275-301.
How to apply: Start date for this project will be 1st October 2018 (or later by agreement). Please make an online application for this project at http://www.bris.ac.uk/pg-howtoapply. Please select Cellular and Molecular Medicine PhD 3yr on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form. For general enquiries linked to the online application process, please email email@example.com.
Candidate requirements: 1st or 2:1 equivalent at master level in electrical & electronic engineering, computer science, maths, or biomedical related subject.
Funding: Fight for Sight, UK.
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