PhD Studentship - Developing automated tools for visual assessment (Nottingham)

Vacancy Reference Number
SCI2063
Closing Date
25 Apr 2022
Salary
Stipend (approximately £16,062)
Address
School of Mathematical Sciences and School of Psychology, University of Nottingham
Duration
36 months

About the PhD

Contrast sensitivity and visual acuity are key indicators of real-world visual performance and reliable biomarkers for a range of ocular diseases. However, current clinical tests rely on repeated subjective responses from the patient, making them unsuitable for use in paediatric and older adult populations, or any situation where cognitive impairments limit response accuracy.

This project will take a fundamentally different approach to the assessment of visual function, exploiting changes in the patterns of miniature, involuntary eye movements to develop automated, objective measurement tools that operate without the need for any overt patient response. Building on strong proof of concept demonstrations and a substantial newly collected dataset, the project will seek to develop a statistical machine learning pipeline that yields precise and accurate assessment biomarkers of visual performance in a time-efficient manner allowing technology adoption.

The studentship is jointly funded by the Schools of Mathematics and Psychology and will provide a stipend at the current UKRI rate to cover living costs (approximately £16,062) and cover Home University fees (estimated at £4,496) for the duration of the project and thesis writing (36 months).

The project will suit a student with a strong quantitative background and interest in applying cutting edge data science techniques to real-world problems.

A good undergraduate degree (minimum 2:1 or equivalent) or Masters (or equivalent) in a relevant field such as Psychology, Mathematics, Neuroscience or Computer Science is essential. Programming skills in Matlab, Python and/or R are desirable.

 

Informal enquiries can be directed to Yordan Raykov (Yordan.Raykov@nottingham.ac.uk) or Neil Roach (Neil.Roach@nottingham.ac.uk).