PhD studentship in Effective Video Action Recognition with Weak Supervision at City
|Published||March 12, 2023|
|Location||London, United Kingdom|
PhD studentship in Effective Video Action Recognition with Weak Supervision at City, University of London in collaboration with Tesco
We are seeking to appoint one fully funded PhD student in Computer Science in collaboration with Tesco Ltd, the largest retail company in UK.
- Closing application date: 15th April 2023
- Starting date: 1st July 2023
The successful candidate will work on exciting project to develop cutting edge computer vision and machine learning technology. Supervised deep learning approaches have demonstrated highly successful performance in video action recognition. Main disadvantages of the supervised models critically rely on large datasets gained from expensive human annotation. This motivates us to look beyond the supervised paradigm as supervised methods frequently suffer from many weaknesses. This project aims to leverage weak supervision to develop good quality supervision for effective action recognition, where alleviates the burden of obtaining hand-labelled data sets.
PhD is sponsored by City, University of London and Tesco. It will provide golden opportunity to work on mass scale real life retail data from Tesco.
What is offered:
The full studentship consists of a full fee cost (UK or international), a maintenance grant of full fees + £19,668 pa, for three years.
The successful applicant will work closely with world leading computer vision and machine learning researchers from City University of London and Tesco.
Hours: full time
The studentship will be awarded based on academic achievement and the potential to produce cutting edge research. Prospective applicant must:
- Hold a good Master’s degree (no less than a second-class honours degree or an equivalent qualification) in Computer Science, Artificial Intelligence, Mathematics or other relevant disciplines. We will also consider applications from those with a good honours degree or extensive professional experience in the area;
- Proficiency in two or more of the following areas:
- implementation and evaluation of deep learning architectures and algorithms.
- computer vision methods and models;
- deep learning in theory and practice.
- Solid mathematical ability
- Proficiency in programming in Python;
- Be able to demonstrate proficiency in the use of oral and written English.
How to Apply:
You are strongly encouraged to discuss your application in advance with Professor Jerry Shen (email@example.com) and Professor Rajkumar Roy (firstname.lastname@example.org).