1 x Postdoctoral Research Assistant in Computer Vision (Ref: 09156/KR)
1 x PhD Studentship in Computer Vision (Ref: 09156/CompSci)
Applications are invited for a full-time Postdoctoral Research Assistant position and a PhD Studentship to undertake research within the context of an UK EPSRC-funded project ‘Multi-Object Video Behaviour Modelling for Abnormality Detection and Differentiatio’.
The project aims to develop the underpinning capabilities for an innovative intelligent video analytics system for monitoring object behaviour captured in vast quantities of surveillance videos and detecting/predicting any suspicious and abnormal behaviour that could pose a threat to public safety and security. The successful candidate will develop models and algorithms for real-time detection and differentiation of abnormalities in complex video behaviours that involve multiple objects interacting with each other.
The successful candidate will be based at the Queen Mary Vision Laboratory, one of UK's leading research laboratories in computer vision, working under the supervision of Dr. Tao Xiang and also closely with Prof. Shaogang Gong in the School of Electronic Engineering and Computer Science, Queen Mary University of London. The Queen Mary Vision Laboratory, led by Prof. Shaogang Gong, currently undertakes research on video behaviour analysis and abnormality detection, people detection and tracking in crowded scenes, video object super-resolution for face recognition, human facial expression and body language modelling, video-audio avatar, dynamic scene background removal and object categorisation.
Postdoctoral Research Assistant in Computer Vision (Ref: 09156/KR)
Candidates must demonstrate the ability for undertaking original research. They should have a PhD (or have submitted their thesis) in computer vision, machine learning, or a related field. They should also have a proven track record on publications in computer vision and/or machine learning. Strong programming skills in Matlab and C++ are required. Experience in real-time processing of video data will be an advantage.
The position is for 3 years starting from 1 August 2009 or as soon as possible thereafter. The starting salary will be in the range of £30,079 - £33,492 per annum inclusive of London Allowance.
The successful candidate must be able to demonstrate his/her eligibility to work in the UK in accordance with the Asylum and Immigration Act 1999.
PhD Studentship in Computer Vision (Ref: 09156/CompSci)
The candidates should have a first or upper second honours degree or equivalent in Computer Science, Electronic Engineering, Mathematics, Physics, or a related field, and be able to demonstrate strong problem-solving and analytical skills. Good programming skills are required, preferably with Matlab and C++. Research experience in image processing, computer vision, or machine learning is desirable.
The studentship is for 3 years starting from 1 August 2009 or as soon as possible thereafter. It includes tuition fees and a tax-free stipend in line with EPSRC recommendations (currently at £14940 per annum for the 2008/09 session), and is available to candidates of all nationalities.
Informal enquires can be made by email to Dr Tao Xiang.
To apply for the Postdoctoral Research Assistant position please email a completed application form, a CV listing all publications, three representative publications in PDF format, and a research statement describing previous research experience and outlining its relevance to this project to Dr. Tao Xiang AND Mrs. Sue White (email@example.com). Please also arrange to send three independent reference letters directly to Tao Xiang AND Sue White via email. Postal applications can be sent to Sue White, School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London, E1 4NS.
To apply for the PhD studentship please email the following documents to Dr. Tao Xiang: a completed application form, a CV listing all publications, your representative publications in PDF format, two independent reference letters, and other relevant documents as requested (see here). These documents must also be provided in paper form and sent to the Admissions and Recruitment Office (see the application form for address).
The closing date for all applications is Wednesday 1st July 2009.
Interviews are expected to take place during w/c 6th July 2009.
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