Project DetailsThe difficulty to obtain a reliable and robust model for quantitative information in real-time has been a major barrier for performing biomedical diagnostics. Most research to-date has focussed on the use of multivariate statistical modelling approach for data analysis, which only yields limited information on physical attributes of the sample such as the size and packing of particulates which could be link to critical physiological conditions.
The project will focus on the development of novel multi-sensor measurement-analysis platform which integrate optics (instrument configuration) and theories of light propagation through particulate media to extract physical and chemical information of biological suspensions. It will exploit spectroscopic techniques of complementary nature to capture richer information in the complex biological suspensions, and utilise the information to provide enhance the model reliability and robustness in diagnosis.
This innovative research project works with world leading experts, ideally suited to students with the creativity and drive to pursue doctoral studies at a technologically leading university. Experience in fermentation reaction or optics, and computational and analytical skills, is desirable although not essential.
In addition to undertaking cutting edge research, students are also registered for the Postgraduate Certificate in Researcher Development (PGCert), which is a supplementary qualification that develops a student’s skills, networks and career prospects.
Funding DetailsThis PhD project is initially offered on a self-funding basis. It is open to applicants with their own funding, or those applying to funding sources. However, excellent candidates will be eligible to be considered for a University scholarship.
Primary supervisor - Dr Yi-chieh ChenSecondary supervisor - Dr Leo Lue
Ms Jacqueline Brown
+44(0) 141 574 5319
James Weir Building, 75 Montrose Street, Glasgow, G1 1XJ
How to applyApply for this PhD project here.
Please quote the project title in your application.