Deep learning for sign language recognition and translation
The studentship will apply deep learning and modern Artificial Intelligence (AI) to the topic of visual language, specifically sign language.
Start date1 October 2023
Funding sourceUniversity of Surrey
A stipend of £17,668 p.a. for 2023/24, which will increase each year in line with the UK Research and Innovation (UKRI) rate, plus Home rate fee allowance of £4,500 (with automatic increase to UKRI rate each year). The studentship is offered for 3 years. For exceptional international candidates, there is the possibility of obtaining a scholarship to cover overseas fees.
The project will research and develop new approaches at the interface between computer vision and neural machine translation with the fundamental goal of addressing automatic recognition and translation of sign language to spoken language. In addition to excellent numerical and programming skills, previous experience in deep learning, NMT, computer vision and sign language would be highly advantageous.
This project is under the supervision of Professor Richard Bowden who runs the cognitive vision lab within the Centre for Vision Speech and Signal Processing. He has a long-standing international track record of work covering many areas of computer vision and machine learning which include visual tracking and the location, tracking, and understanding of humans. You will be joining a thriving research group with ongoing projects into perception for autonomous vehicles, sign language recognition/production and robotics and AI.
We acknowledge, understand and embrace diversity.
Related linksRichard Bowden's webpage
All applicants should have (or expect to obtain) a first-class degree in a numerate discipline (mathematics, science or engineering) or MSc with Distinction (or 70% average) and a strong interest in pursuing research in this field. Additional experience which is relevant to the area of research is also advantageous.
Non-native English speakers will be required to have IELTS 6.5 or above (or equivalent) with no sub-test of less than 6.
How to apply
In the first instance, please send your CV, covering letter and degree transcripts to firstname.lastname@example.org.
Interested applicants should contact email@example.com at the first available opportunity and not wait until the deadline.
For more information visit the Centre for Vision, Speech and Signal Processing programme page.
Read our studentship FAQs to find out more about applying and funding.