PhD Studentship: PhD in Computer Vision and Deep Learning

If you think you might like to specialise in AI and specifically in deep learning, computer vision, differentiable rendering or computational linguistics then this fully funded studentship may be for you.

The work will involve the use of Natural Language Processing (NLP), Computer Vision (CV) and Machine Learning (ML) for the translation between Sign Languages and spoken language. It will include the application of NMT techniques and Large Language Models (LLMs).

In addition to excellent numerical and programming skills, previous experience in deep learning, pytorch, computer vision, neural machine translation, large language modelling 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.

Supervisor: Professor Richard Bowden

Entry requirements

Open to candidates who pay UK/home rate fees. See UKCISA for further information.

Starting in July 2024. Later start dates may be possible, please contact Professor Richard Bowden once deadline passes.

You will need to meet the minimum entry requirements for our Vision, Speech and Signal Processing PhD programme.

Please note: This opportunity is also open to international candidates of an exceptionally high calibre.

How to apply

Applications should be submitted via the Vision, Speech and Signal Processing PhD programme page.

In place of a research proposal, you should upload a document stating the title of the project that you wish to apply for and the name of the relevant supervisor.

Funding

Funding is for 3 years. Fully and directly funded for this project only.

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