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 do 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 running a research program 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, osteoporosis, obesity and stroke, as a consequence of a rapidly aging population with mobile digital technologies, covering the value chain from acute care to patient's private homes.
There is ample evidence showing that majority of hip fractures in the elderly population are associated with a short, low-trauma fall. Elevated hip fracture risk is generally addressed either pharmacologically or through lifestyle interventions. While both have been moderately successful, they can be expensive and difficult to implement but pharmacological treatment also carries its own risks. For this reason, clinicians must carefully screen for risk before implementing these solutions, and how this screening is informed is critical to their success. Presently, areal bone mineral density (aBMD) is the clinical 'gold standard' used to diagnose those with osteoporosis. Epidemiologic evidence supports that low BMD is associated with increased population-based risk of fracture, however, aBMD and other clinical assessment tools are not sensitive enough to identify individuals likely to suffer a fracture.
With this project, we aim to address the limitations of current screening methods and develop novel, subject-specific computer models for diagnosing hip fracture risk and novel methods for preventing fractures from occurring. The proposed research will combine, image processing of large cohort databases, dynamic Finite Element Analysis, in-silico clinical trials and data driven methods to achieve the goals of the project.
The post-doctoral researcher will enter a team of researchers that is working on improving the management of the risk of injurious falls in Singaporean elderly.
As a post-doctoral researcher in the FHT program, you will be responsible for:
Candidates with a PhD or equivalent in Mechanical Engineering, Electrical Engineering, Computer Science, Automotive Engineering, Civil Engineering, Biomedical Engineering, or related fields are encouraged to apply. Experience with any of the following would be a distinct advantage: bone mechanics, image analysis, statistical shape databases, programming (e.g. Python, C++, Matlab), pre-processing for explicit Finite Element Analysis (in e.g. Ansa) and use of commercial Finite Element solvers (e.g. LS Dyna, Ansys, Abaqus). Funding is available for two years with a potential extension. Applications will be accepted until the position is filled. The workplace is at the SEC in Singapore.