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. This is a fully-funded PhD studentship with annual bursary of £16,000. Tuition fees are paid by the University. Brief Project Description 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 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. The successful candidate will be responsible 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. Application Process: To apply please request an application pack by emailing [email protected], quoting “PhD Studentship in Deep Learning for Modelling Complex Video Activities”. Fully completed applications must be sent to [email protected], by 5pm on Friday 4 October 2019. As part of the application process you must submit your CV, along with a supporting statement (2-page maximum) which explains why you believe you are the best candidate for this studentship. Please be advised that the selection process may involve an interview. Information: For all informal requests contact Prof Fabio Cuzzolin ( [email protected]). Please also consult the Lab’s web site at http://cms.brookes.ac.uk/staff/FabioCuzzolin/.
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