Post Doctoral Research Associate in Computer Vision and Machine Learning

Durham, England
06 Dec 2017
End of advertisement period
04 Jan 2018
Contract Type
Fixed Term
Full Time

Department :

Department Of Computer Science

Position Type :


Grade 6/7 (£25,728 - £34,520)

We are seeking a full-time Postdoctoral Research Associate (PDRA) to join Prof. Toby Breckon's research team at Durham University. The post is funded, for an initial fixed-term period of 18 months, by an ongoing portfolio of research work primarily spanning aspects of automatic image classification (airport security, in collaboration with UK Home Office and US Dept. Homeland Security) in addition to visual surveillance (thermal target tracking, in collaboration with DSTL) and sensing for future autonomous vehicles (in collaboration with Renault).

The researcher will have the opportunity to work on common themes of machine learning research with applications across several funded work stream within the group. They will consider the use of cutting-edge deep learning algorithms for image classification and generalized data understanding tasks (object detection, human pose and behaviour understanding, and materials discrimination), in addition to integrated aspects of visual tracking and stereo vision across a range of image modalities. Specifically, they will investigate novel aspects of automatic adaptability of contemporary machine learning approaches as an aspect of these tasks. They will develop software algorithms, manage their own academic research in addition to project delivery to a range of external industrial and government collaborators.

In addition to published research output, the candidate can expect their research to have significant impact across a range of industrial/governmental collaborators and form a major innovation contributor to future security and vehicle autonomy applications.

The post the offers an outstanding opportunity to gain a strong research track record in an exciting and fast-moving area of applied computer vision and machine learning whilst working in an environment with high levels of external collaboration and industrial research impact.

Further details on the research portfolio can be found on the following websites: 

Closes midday on : 04-Jan-2018