Research Associate/Senior Research Associate in Radar Systems and Wireless Imaging
Division/School School of Computer Science, Electrical and Electronic Engineering and Engineering Maths
Contract type Open Ended
Working pattern Full time
Salary £33,199 - £42,036
Closing date for applications 02-Oct-2019
We are looking for an enthusiastic, self-motivated individual to contribute to the EPSRC-funded OPERA and SPHERE projects within the portfolio of the Digital Health Engineering research group.
The post holder will join “Wireless Sensing Theme” and will be required to make a significant contribution to the field of Digital Health Engineering and to assist with the development, integration and administration of the relevant research activities.
The role-holder will join the Digital Health Engineering research group and will have access to state-of-the-art test and measurement equipment.
The OPERA Project - Opportunistic Passive Radar for Non-Cooperative Contextual Sensing investigates a new unobtrusive sensing technology for contextual sensing - defined as concurrent physical activity recognition and indoor localisation - to facilitate new applications in e-Healthcare and Ambient Assisted Living (AAL). The OPERA platform will be integrated into the “SPHERE long term behavioural sensing machine” to gather information alongside various other sensors around the home so as to monitor and track the signature movements of people.
The OPERA system is be built principally around passive sensing technology: a radar network that detects the reflections of ambient radio-frequency signals from people in residential environments. These opportunistic signals are transmitted from common household WiFi access points, but also other wireless enabled devices which are becoming part of the Internet of Things (IoT) home ecosystem.
The project makes use of additional cutting-edge sensing modalities and hardware. It also leverages the latest ideas in FMCW radar signal processing, Lidar Point Cloud Deep Learning Frameworks, bio-mechanical modelling and machine/deep learning for automatic recognition of everyday activities, poses and ambulation.
Up to 2 posts are available immediately and are offered on a full-time basis for an initial term of two years.
It is anticipated that interviews will take place within 1 month of the closing date.
Informal enquiries can be made to: Professor Robert Piechocki
Digital Health Engineering: http://www.bristol.ac.uk/engineering/research/digital-health/
SPHERE Next Steps: https://gtr.ukri.org/projects?ref=EP%2FR005273%2F1
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.