|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||From £17,668 Home fees (2023/24) included plus an annual stipend paid at the UKRI rate (award for 2022/23).|
|Placed On:||20th September 2023|
|Closes:||16th October 2023|
Project title: GAIA: Generating Artificial Intelligence Assisted Assessment for Alopecia
Project contact: Dr Adrian Davison
Home fees (2023/24) included plus an annual stipend paid at the UKRI rate (£17,668 for 2022/23).
Mode of study: Full time
Eligibility: Open to home & overseas students.
Eligible overseas students will need to make up the difference in tuition fees.
Closing date: 16 October 2023
Expected start: January 2024
The impact of alopecia is highlighted in the Global Burden of Disease estimates of years lost to disability, where alopecia areata (AA) was ranked higher than both psoriasis & melanoma in disease impact.
Irrespective of the underlying cause or pattern of the hair loss (diffuse thinning or patches), accurate measures of a person’s hair loss are difficult. Before significant diffuse hair thinning becomes clinically appreciable, over 50% scalp hairs need to be lost. Therefore, the process may have been occurring for many months or years before someone presents to their doctor. Current treatments are reasonable at stabilising hair loss but not very good at reversing it. Therefore, being able to identify the problem and treat early in the course of the disease would result in better outcomes for the patient.
We are looking for candidates to research computer vision & artificial intelligence techniques to create an objective method of measuring areas of hair loss/recovery. This will tackle the problems of current technology, where it can be time-consuming, expensive, or require shaving of a patient’s hair.
The successful candidate will benefit from training facilities at Manchester Metropolitan University & The Dermatology Centre, University of Manchester, Salford Royal NHS Foundation Trust.
Aims and objectives
The aim of this project is to predict the rate of hair loss or recovery in people with alopecia using computer vision & Artificial Intelligence (AI) algorithms.
To achieve this aim, the main objectives are:
Specific requirements of the project
Candidates must have a strong motivation for research and excellent programming skills. Expertise of developing computer vision & machine learning algorithms would be desirable, with an interest in image analysis.
How to apply
Interested applicants should contact Dr Adrian Davison for an informal discussion.
To apply you will need to complete the online application form for a full-time PhD in Computing and digital technology (or download the PGR application form), by clicking the 'Apply' button, above.
You should also complete the PGR thesis proposal (supplementary information) form addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest.
If applying online, you will need to upload your statement in the supporting documents section, or email the application form and statement to mailto:PGRAdmissions@mmu.ac.uk.
Please quote the reference: SciEng-AD-2023-GAIA
Type / Role: