Research Associate/Senior Research Associate in Video Monitoring, SPHERE Project

Bristol, United Kingdom
£32,548-£36,613 (Grade I) £36,613-£41,212 (Grade J)
04 Dec 2018
End of advertisement period
16 Dec 2018
Contract Type
Full Time

Division/School School of Computer Science, Electrical and Electronic Engineering and Engineering Maths
Contract type Open Ended
Working pattern Full time
Salary £32,548-£36,613 (Grade I) £36,613-£41,212 (Grade J)
Closing date for applications 16-Dec-2018

Please Note: This is a “rolling advert” with a nominal close date only.  Applications are welcome at any time and the timing of the selection process will be dependent on the applications received. 

An interdisciplinary research collaboration (IRC) led by the University of Bristol together with the Universities of Southampton and Reading, was awarded a grant in 2013 by the Engineering and Physical Sciences Research Council (EPSRC) of around £12 million.  They worked in partnership with Bristol City Council, IBM, Toshiba and Knowle West Media Centre (KWMC).

The collaboration, known as SPHERE (Sensor Platform for HEalthcare in a Residential Environment), developed home sensor systems to monitor the health and wellbeing of people living at home. In October 2018, the Sphere Next Steps project will enhance and extend the achievements of SPHERE and will primarily be focussed on the analysis of the health monitoring data captured at people’s home. For example, the data will include subjects recuperating from a variety of ailments. With one RA already in place, the Visual Monitoring workpackage in the project is seeking to employ a second RA for a period of 2 years.  

The successful candidate will work together with several academic staff and the existing RA in a team to investigate algorithms and models for analyzing and understanding human behaviour and activity and behaviour, gait and facial and emotion expression in cluttered and uncontrolled home environments. The research and software development will involve feature detection and tracking, deep learning techniques, statistical modelling and analysis, the use of one or more cameras, and many other relevant topics. The post involves close collaboration with other SPHERE project personnel – from other workpackages within the project, including integration of other sensors, data fusion and data mining.

The candidate should:

Hold (or be currently in the completion stages of) a PhD degree in Computer Science or Electronic Engineering or a related discipline, in a field related (but not limited) to computer vision, machine learning, statistics or applied mathematics.

Ideally also have experience in any one or more of the following: human tracking; multi-camera analysis; action and event recognition; object detection and recognition

Have excellent C/C++/Matlab/Python programming and systems integration skills

Have a good publication record in computer vision and/or machine learning

Should be able to conduct research independently

Possess excellent speaking and writing skills in English. 

This position is offered on a full time, open-ended contract, with funding for up to 2 years in the first instance, with the potential for a further extension. 

There is no formal closing date, but the start date for each post is flexible dependent on the circumstances of the successful candidates.

For further details and application please contact:

Prof. Majid Mirmehdi - Email:

The University is committed to creating and sustaining a fully inclusive culture.  We welcome applicants from all backgrounds and communities.

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