Are you interested in developing next-generation sensing technologies for unobtrusive sleep and physiological monitoring? In this role, you will contribute to research that uses radar and complementary sensing technologies to monitor sleep and related physiological signals in living-lab and home-like environments. You will work as part of a multidisciplinary team developing algorithms, experimental methods and research prototypes that could support future technologies for dementia care, sleep health and long-term remote monitoring.
You will develop and evaluate signal processing and machine learning methods for interpreting radar and multimodal physiological data. Your work will focus on extracting meaningful sleep and physiological information from unobtrusive sensing systems, including respiration, cardiac activity, body movement, sleep posture and sleep-related events.
You will help design and run validation studies with human participants, including the collection and analysis of data from radar, sleep monitoring systems and reference physiological measurements. You will also contribute to the development and refinement of research prototypes, including radar systems, under-mattress or contactless sensing devices, and associated data acquisition pipelines.
We are looking for a motivated and collaborative researcher with experience in one or more of the following areas:
1. A PhD in Electronic Engineering, Biomedical Engineering or Computer Science.
2. Experience in signal processing and machine learning for physiological, biomedical, radar, wearable, contactless or multimodal sensor data.
3. Experience with radar systems.
4. Strong programming skills, for example in MATLAB, Python or equivalent tools.
5. An interest in sleep monitoring, remote sensing, dementia care technologies or long-term health monitoring.
6. Excellent written and communication skills.
7. Ability to work independently, manage competing deadlines and collaborate effectively.
8. The opportunity to continue your research career at a world-leading institution.
9. The opportunity to work within a collaborative and multidisciplinary research environment.
10. The opportunity to contribute to research with real-world translational potential.
11. Access to expertise and collaborations across Imperial College London, the UK Dementia Research Institute Care Research & Technology Centre, the University of Surrey and wider academic and clinical networks.
12. Opportunities to publish in high-quality journals, present at national and international conferences, and contribute to grant proposals and future research directions.
13. Opportunities to develop skills in radar sensing, physiological signal analysis, experimental design, machine learning, and prototype development.