Research Associate or Senior Research Associate in Video Monitoring - ‘‘SPHERE'' Project
- Employer
- Global Academy Jobs
- Location
- United Kingdom
- Closing date
- Sep 5, 2018
View more
- Sector
- Science, Computer Science and IT, Computer Science, General Computing, Physical Sciences and Engineering, Chemical Engineering, Chemistry
- Hours
- Full Time
- Organization Type
- University and College
- Jobseeker Type
- Academic (e.g. 'Lecturer')
Job Details
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.
Application
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.
For further details and application please contact:
Prof. Majid Mirmehdi - Email: m.mirmehdi@bristol.ac.uk
The University is committed to creating and sustaining a fully inclusive culture. We welcome applicants from all backgrounds and communities.
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