Funding
Self-funded
Project code
COMP5401021
Department
School of ComputingStart dates
October, February and April
Application deadline
Applications accepted all year round
Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.
The PhD will be based in the School of Computing and will be supervised by Dr Ioannis Kagalidis.
The work on this project could involve:
- Working with real time or near real time image identification.
- Working in developing innovative Artificial Intelligence solutions.
- Evaluate the performance and behaviour of different approaches to semantic image identification.
Neural Networks have proven to be effective in image recognition tasks. The ability to extract semantic information from near real time images is still somewhat not fully explored and still remains relatively elusive. Humans are able to recognise objects and their path through space in real time. Consider cars that wait at a red traffic light. Humans are able to pick one and follow it through to the next traffic light. For a standard AI system, any car is the same as the next. Semantic identification will almost certainly become a necessity in applications coping with the need to understand concepts as abstract as 鈥渇ollow that yellow car鈥 and 鈥渉as the accident completely blocked the motorway?鈥 which would provide a high level of interaction between humans and AI systems. The School of Computing in the 黑料入口 has an established and ongoing collaboration with the PCC and private stakeholders to investigate the application of Neural Networks in better traffic managements and generation of traffic flow models.
Fees and funding
Visit the research subject area page for fees and funding information for this project.
Funding availability: Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the UK (UK and EU students only).
Bench fees
Some PhD projects may include additional fees 鈥 known as bench fees 鈥 for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.
Entry requirements
You'll need a good first degree from an internationally recognised university or a Master鈥檚 degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
- Basic understanding of Artificial intelligence concepts.
- Capable to carry out independent research.
- Capable to carry out simulations and Artificial Neural Network code development and testing.
- Capable to prepare research articles.
How to apply
When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our 鈥How to Apply鈥 page offers further guidance on the PhD application process.