Location: | Coventry |
---|---|
Salary: | £35,333 to £44,737 per annum |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 25th November 2022 |
---|---|
Closes: | 9th January 2023 |
Job Ref: | REQ010223 |
Package
As one of Coventry's biggest employers, we offer some pretty impressive benefits including an excellent pension scheme and generous holiday allowances.
Basis: Full time
Job category/type: Research
Coventry University is seeking a Research Fellow for an Engineering & Physical Sciences Research Council (EPSRC) project “RADAR Sensing for Human Activity Monitoring of Daily Living Simultaneously in Multiple Subjects” to work in the Research Centre for Intelligent Healthcare.
Job description
The Centre aims to become a globally recognised research centre for pioneering and opinion-setting research in the area of digital healthcare and its contribution to improving communities and enriching and prolonging individual lives.
The post-holder will work with Dr Syed Aziz Shah (Project Lead & Principle Investigator) within one of the six vibrant teams namely “Healthcare Sensing Technology Cluster” supporting the delivery of the project.
Project description:
State-of-the-art RADAR systems have only been used to detect the human activities of daily living of single individuals in direct line-of-sight (LOS) and in a well-controlled environment [1],[2]. In this project, we will develop a novel approach of using RADAR sensing technology coupled with machine learning/deep learning algorithms for not only detecting, but also identifying and tracking the activities of daily living of multiple individuals in an indoor environment. Specifically, the approach aims to capture critical events (such as falls and wandering behavior) in direct line-of-sight and non-line-of-sight in a well-controlled controlled environment, and in a number of natural heterogeneous environments in a non-intrusive way.
[1]. S.A. Shah and F. Fioranelli, “Human Activity Recognition: Preliminary Results for Dataset Portability using FMCW RADAR”, International RADAR Conference, France 2019.
[2]. F. Fioranelli, S.A. Shah, et al., “Intelligent RF Sensing for Falls and Health Prediction http://researchdata.gla.ac.uk/848/”, Dataset, 2019
The post is a fixed term position, subject to funding
If you are interested in the position and wish to know more, please contact Dr Syed Aziz Shah ( syed.shah@coventry.ac.uk ).
To view Job Description and Person Specification please click here
Type / Role:
Subject Area(s):
Location(s):