[Comp-neuro] PhD studentship: Rapid Bacteria Colony Counting Algorithm Development
v.steuber at herts.ac.uk
Fri Oct 5 13:03:17 CEST 2018
PhD Studentship: Rapid Bacteria Colony Counting Algorithm Development
?Biocomputation Research Group , University of Hertfordshire and Synoptics Limited, Cambridge
The University invites applications for a PhD student to join our Hertfordshire Knowledge Exchange Partnership (HKEP) scheme. This four-year project requires a PhD student to undertake a collaborative research project with support from University academic supervisor(s) and company scientists.
The project begins with a Knowledge Exchange year in which you are based in the company. Successful completion of the first year will require the submission of a scientific report, research proposal and an oral examination. The successful candidate will then begin a three-year PhD research project in an area of interest to the company.
Start date: January 2019
Duration: Four years
Company: Synoptics Limited, Cambridge
Stipend: Starts at £15,220 per annum plus approved expenses. All students will also receive a maximum contribution towards their individual tuition fees that is equivalent to the Home/EU student fee in each year of registration.
Bacterial colony counting is widely used in both industry and research laboratories in a wide range of applications; these include quality control, environmental monitoring, immunological studies and medical testing. The number of colonies on an agar plate can be used to estimate the number of viable bacteria (total viable count) present in a test sample. This can then be used as an indicator of the cleanliness of a surface, the sterility of a product or the presence of a bacterial infection.
Traditionally, colony counting was performed manually or using a light box which was time-consuming and prone to human error. The advent of automated colony counters, which use sophisticated algorithms to detect and count colonies based on shape or colour, has overcome these drawbacks. The popular technologies exploited for bacteria colony counting are edge detection techniques for image processing.
However, a number of challenges remain in automated colony counting: identifying and splitting touching colonies, background noise, colony density variance etc. Hence, more advanced and sophisticated techniques need to be developed to cope with these issues while taking efficiency into account. The aim of this project is to propose and implement new algorithms which are robust to noise for rapid bacterial colony detection and counting.
Dr Na Helian
Dr Yi Sun
Dr Peter Lane
Mr Richard Hopwood
For further information and to apply for this role please email hsp at herts.ac.uk. The deadline for applications is 31st October 2018. Informal enquires should be addressed to Dr. Na Helian (n.helian at herts.ac.uk). Please note that applications sent directly to these address will not be accepted.?
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