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PhD Studentship in Deep Learning for Modelling Complex Video Activities

  • Full or part time
  • Application Deadline
    Friday, October 04, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Eligibility: UK ,EU & International candidates
Bursary: £16,000 per year (no annual inflation increase)
Fees: Tuition fees will be paid by the University
Deadline for applying: Friday 4 October 2019
Start date: January 2020

Primary supervisor: Professor Fabio Cuzzolin

Short Introductory Paragraph
The Faculty of Technology Design and Environment at Oxford Brookes University is pleased to offer a three-year full-time PhD studentship to a new student commencing January 2020. The successful candidate will work within the Visual Artificial Intelligence Laboratory, under the supervision of Professor Fabio Cuzzolin.

Full Project Detail
The Visual Artificial Intelligence Laboratory is one of the top research groups in deep learning for action detection. In 2017 we designed the first system able to localise multiple actions in a video in real time. The Laboratory is running on a budget of around £1.5 million, with six live funded projects, and is projected to comprise 20/25 people in 2020. We closely collaborate with Oxford University, Cambridge University, IIT Bombay, and others.

The successful candidate will contribute to the research conducted under a new Research Agreement with Huawei Technologies on “Deep learning for complex activity recognition”. The project aims to explore new deep learning models of complex activities composed by multiple events/actions, such as cooking a meal, or autonomous driving scenarios involving, e.g., multiple vehicles negotiating an intersection.

The successful candidate will be required to:
- Develop new deep learning models for the detection of complex video activities.
- Carry out their experimental validation.
- Collaborate with the other members of the Laboratory.
- Liaise with our industrial and academic partners
- Conduct literature searches and reviews, lead the preparation of research papers for publication, and communicate results at conferences and workshops

Find out more
Please also consult the Lab’s web site at http://cms.brookes.ac.uk/staff/FabioCuzzolin/.

Entry requirements:
The essential selection criteria include:
- A good first degree in Machine Learning, Computer Vision or related fields.
- Experience in Machine Learning applied to Computer Vision.
- Good coding skills in Python, Matlab and/or C++.
- Ability to work independently or as part of a team.
- Excellent written and oral communication and organisational skills.

The desirable selection criteria include:
- Experience and knowledge of deep learning techniques.
- Experience in action and activity recognition or video processing.
- Experience of coding in Torch, Tensorflow or Caffe.
- A track record of research publications in Computer Vision or Machine Learning.

Contact details:
For all informal requests contact Professor Fabio Cuzzolin ().

How to apply:
To apply please request an application pack by emailing: quoting “PhD Studentship in Deep Learning for Modelling Complex Video Activities”.

As part of the application process you must submit your CV, with a supporting statement (2-page maximum) which explains why you believe you are the best candidate for this studentship.

How good is research at Oxford Brookes University in Computer Science and Informatics?

FTE Category A staff submitted: 13.00

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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