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Adaptive time-resolved optical imaging for medical applications


   College of Medicine and Veterinary Medicine

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  Dr Gareth Williams, Dr J Hopgood  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

·        Background

Optical imaging is rapidly becoming a key tool in medical procedures to aid clinicians. Fluorescence, fluorescence lifetime and Raman provide approaches to interrogate optical “fingerprints” of disease states and provide information on areas such as drug-target engagement, in real time and shorten pathways to diagnosis and treatment. There are significant challenges with current implementations of scanned optical imaging systems which rely on coherent imaging fibre bundles to access a desired sample location, namely imaging speed and signal to noise and data volume. We propose that the use of adaptive optical scanning (spatially, temporally and spectrally), combined with new image processing will increase the signal to noise, speed of acquisition and information content of minimally invasive optical imaging.

·        About the Project

This PhD position looks to use advanced optical imaging techniques to develop new methods for accessing optical “fingerprints” of disease, tailored to translatable medical applications. We are seeking an outstanding physics/engineering/computing student with great interest in understanding scanned optical image generation and processing to design and develop novel new adaptive image acquisition algorithms and image processing methods.

Advanced time resolved imaging technologies will be utilized to enable adaptive scanning (temporally, spatially and spectrally) of complex samples to reduce sampling time whilst increasing signal to noise. This will be applied to samples imaged both on free space microscopes and imaged through coherent imaging fibre bundles, both with unique challenges to data acquisition, reconstruction and analysis of multidimensional signals. A particular requirement for many translational applications is real-time high speed image acquisition and processing. This ideally requires a minimal sampling approach which can be enhanced through frame-to-frame adaptation of acquisition parameters and on-the-fly region of interest optimization. There will be the opportunity to apply the techniques developed to innovative imaging platforms designed specifically for clinical translation and on a range of relevant tissue samples.

You will be based within the interdisciplinary Translational Healthcare Technologies group with biologists, chemists, physicists, machine learners and clinicians.

The research group is located in the University of Edinburgh Centre for Inflammation Research; a world-class research environment at the interface between biological and medical science, with multidisciplinary groupings focused on inflammation, infection, disease and repair. The Centre is based within the Edinburgh Medical School in the outstanding facilities of the Queen’s Medical Research Institute at the site of the Royal Infirmary of Edinburgh hospital, maximising future translational opportunities. You will further be working closely with the School of Engineering drawing on expertise in signal and image processes.

As part of the application process, please fill and submit the online application form.


Funding Notes

The successful applicant will be awarded a 4 year studentship, which includes their stipend at the UKRI rate (AY 2022/23: £16,062), tuition fees, and contributions towards travel and research costs for their PhD project.
The studentship will be awarded competitively.
Applicants should hold at least an upper second class degree or equivalent in a relevant discipline (eg physics, engineering, computing). Applicants should submit the following documents: (i) Personal statement about their research interests and their reasons for applying and (ii) CV.

References

Applicants should also arrange for two academic referees to submit letters of reference via email before the deadline.
All documents should be submitted to CIR.Postgraduate@ed.ac.uk no later than 5pm on the 13th June.
Short-listed candidates will be notified by email.
Informal enquiries can be sent via email to G.O.S.Williams@ed.ac.uk

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