Post Doctoral Researcher - Future Health Technologies on assessing loading conditions during walking in elderly adults in Zürich

100%, Singapore, temporary

ETH Zurich is one of the leading universities of the world with a strong focus on science and engineering. In 2010 it established the Singapore-ETH Centre (SEC) in collaboration with the National Research Foundation (NRF) to conduct interdisciplinary research on pressing problems.

In collaboration with the National University of Singapore (NUS), the Nanyang Technological University (NTU), Duke - NUS, the National Health Group (NHG), National University Health System (NUHS), and SingHealth, SEC is undertaking a research programme on "Future Health Technologies (FHT)". It addresses some immanent health challenges by developing a future-oriented Mobile Digital Health Concept that tackles the increase in patients suffering from chronic diseases such as diabetes, obesity and stroke, as a consequence of a rapidly ageing population with mobile digital technologies, covering the value chain from acute care to patients' private homes.

Our Module within FHT addresses  injurious falls can be most effective. The aim of the umbrella Project, placed within our Module, is to provide an assessment of fall risk in a personalised manner via the use of wearable technology. The approach combines the state-of-the-art multipoint wearable sensor systems () with comprehensive neuromuscular model for movement (). As part of this PostDoc project, we aim to establish an understanding of the loading conditions and the involved mechanics associated with walking from the wearable sensors. Such characterisation will allow us to address age-related decline in the mechanics involved during task performance and its association with injurious falling.

Gait data from multiple sensors will be collected while the elderly individuals walk for a short period of time. The focus here will be to provide an interpretation of the loading conditions associated with walking from the wearable sensors (but also with floor mounted inertial measurement unit - IMU sensors). In addition, the spectral analyses of the wearable- (sensor-) based kinematic signals during walking will provide a comprehensive evaluation of the dynamics involved in gait. Finally, a relationship between the loading conditions and gait features extracted from the machine learning techniques will allow a comprehensive evaluation of the involved mechanics during walking in elderly adults.

The duration of employment is for 1 year. The earliest starting date for the position is the 1st February 2021. If it is necessary for the applicant to apply for a work permit in Singapore, a later starting date is expected.

• A PhD in biomedical and other engineering fields, or physics
• At least a year of experience in a postdoctoral or leadership position after completion of the PhD
• Considerable experience in signal processing on inertial measurement unit style sensor datasets
• Experience in aspects of experimental design, but extraction, and estimation of loading conditions (and mechanics) from task performance
• Basic understanding of multivariate statistics especially in relation to bioengineering applications is needed
   
• Programming skills: Considerable experience/expertise in Python and/or R (but also Matlab). Previous experience with movement datasets from wearables is necessary. Previous experience with machine learning techniques is desired.
• Personal: Are you motivated to work on challenging problems? Can you work independently on a project level demonstrating problem solving skills? Do you see yourself fitting in with the team of scientists? If yes, this job might just be for you.

The Singapore-ETH Centre provides a multicultural and interdisciplinary environment to researchers working on diverse themes focussed on sustainable and liveable cities, resilient urban systems, and patient-centric healthcare. The centre is home to a community of over 100 doctoral, postdoctoral and professorial researchers working in three main programmes: Future Cities Laboratory, Future Resilient Systems, and Future Health Technologies.