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Signal Processing and Machine Learning for microendoscopy sensing for in vivo pharmacology

Project Description

As part of a recently awarded EPSRC grant, in partnership with GSK, we are seeking an engineering student with strong signal processing, image processing or machine learning qualifications and skills to develop algorithms to improve the quality of data received from an imaging and sensing system called Kronoscan. There is an emphasis on developing robust real-time algorithms which can be translated in clinical applications.
You will join an interdisciplinary team, comprising signal processing, electrical engineering, chemistry, biology and clinical science and will work with teams based within the Queen’s Medical Research Institute in the Centre for Inflammation Research. The aim of the overall project is to develop new technologies to understand and evaluate disease and drug effectiveness in model systems.

Funding Notes

The successful applicant will be awarded a 3 year studentship, which includes their stipend and tuition fees at the UK/EU rate, 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. Applicants should submit the following documents : (i) Personal statement about their research interests and their reasons for applying; and (ii) CV.


Applicants should also arrange for two academic referees to submit letters of reference via email before the deadline. All documents should be submitted no later than 5pm on Monday 21st October 2019. Short-listed candidates will be notified by email.
Informal enquiries can be sent via email to [email protected]

How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)

FTE Category A staff submitted: 91.80

Research output data provided by the Research Excellence Framework (REF)

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