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3-year funded PhD opportunity

Mathematical Sciences

Location:  UK Other
Closing Date:  Sunday 09 April 2023
Reference:  SCI5152

We are currently recruiting a PhD candidate for a project entitled ‘Developing automated tools for visual assessment’. The successful candidate will be jointly supervised by Dr Yordan Raykov (School of Mathematics) and Dr Neil Roach (Visual Neuroscience Group, School of Psychology) at the University of Nottingham.

The Project:

The ability to accurately assess visual sensitivity is vital for detecting eye disease, informing decisions about when to start and stop treatment, and evaluating the effectiveness of interventions. 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 impairment limits 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 Environment:

Nottingham is ideally situated in the middle of England and has excellent transport links, being served by a major train station and with multiple airports close by. The East Midlands is one of the most affordable areas to live in the UK and Nottingham University is situated on a beautiful, leafy campus with easy access to the city centre (15 minute tram ride). 

The School of Mathematical Sciences at University of Nottingham has a long-lasting tradition in statistical machine learning, developing some of the ubiquitous algorithms powering the current AI revolution. The School of Psychology has one of the largest groups of vision scientists in the UK, with expertise spanning a wide range of areas and techniques. Both schools have an established track record of training successful PhD students.

Funding Details:

The studentship is jointly funded by the Schools of Mathematics and Psychology and will provide a stipend to cover living costs (approximately £17,668) and cover Home University fees (estimated at £4,596) for the duration of the project and thesis writing (36 months).

The starting date is from 1st October 2023.

Requirements:

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, Statistics, 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).

How to apply:

All applications are to be made directly to the University, selecting PhD Mathematics (36 months duration) as the course. Please apply at:

https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx.

In the research proposal section please only include “Raykov/Roach advertised PhD position” in the title. You are required to upload the following documents to your application:

  • C.V.
  • Personal statement (maximum 1 page) describing why the candidate is interested in pursuing a PhD and any relevant research experience.
  • Either two references (in a non-editable format such as pdf, on headed paper and signed by the referee) or the details (email addresses) of two referees that we can contact. One of the references must be academic.

If you have any questions about the application process through MyNottingham, please contact sciencessupport@nottingham.ac.uk for further advice.

 

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