Urgent! Postdoc Researcher (2 Years) - T150-01201 BE-FIT SEC Job Opening In singapore, Singapore – Now Hiring Singapore ETH-Centre
Job description
We will investigate movement patterns and features of walking outdoors and in the neighbourhoods among vulnerable older adults (suffering from OA as well as at high risk of falling) in order to understand perceptions on interacting with built environment.
We will acquire these movement patterns and features using the state-of-the-art inertial measurement units (wearables such as ZurichMOVE or Axivity) sensors.
These sensors are equipped with triaxial accelerometers and gyrospcopes and provide assessment of aspects such as impact and swing behaviour during different movements.
Specifically we will be addressing the following research questions:
The general concept is to generate machine learning as well as statistics-based models to extract movement patterns from movement/locomotion/walking/gait dataset collected via wearable sensors.
The gait data from multiple sensors will be collected while participants (older adults) move/walk/transition for both short (up to 10 minutes) as well as long (over multiple days) periods of time.
This data will be complemented with data from our collaborators on walkability assessment, where we evaluate naturalistic observation on individual’s daily routes and outdoor activities.
Finally, we will also tap into questionnaire data involving individuals’ fall history, psychosocial status as well as cognitive ability, as well as their perception of the built environment.
The primary task will be to extract features (gait signatures, but also artificial “machine learned” features) that allow us to assess fall risk in an individualized manner.
Crucial aspects are the interpretability and repeatability of these signatures as these aspects will allow clinical as well as stakeholder uptake.
Another important aspect for uptake is the association (via analysis as well as interpretation) of these features to the walkability as well as clinical assessment to provide a hybrid ‘mapping’ of the manner in which older adults interact with their environment.
Profile
Minimum 2 years of experience in machine or deep learning with a background (PhD) in computer science, computer vision, neuroscience, physics or biomedical and/or other engineering fields.
Expertise in predictive model development, especially for healthcare applications.
A solid understanding in experimental design, feature extraction, selection, and analysis, as well as tailoring machine/deep learning techniques to hybrid datasets including clinical battery, and objective physiological (movement) datasets.
A strong foundation in deep and machine learning algorithms, statistical analysis, and study design from ideation to evaluation and validation.
A strong publication record especially in area of artificial intelligence and machine learning.
Presentations at conferences and participation in workshops is desired.
Programming skills:
Personal:
Workplace
Workplace
We offer
The Singapore-ETH-Centre is an equal opportunity and family-friendly employer.
All candidates will be evaluated on their merits and qualifications, without regards to gender, race, age or religion.
The employment will be at the Singapore-ETH Centre and local working regulations will apply.
We value diversity
In line with to find out how we ensure a fair and open environment that allows everyone to grow and flourish.
Curious?
So are we.
We look forward to receiving your online application with the following documents:
Please note that we exclusively accept applications submitted through our online application portal.
Applications via email or postal services will not be considered.
Further information about BE-FIT Project can be found on our website and Questions regarding the position should be directed to Dr. Navrag Singh email: and Mr. Aaron Ang email: .
Singapore-ETH Centre
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.✨ Smart • Intelligent • Private • Secure
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Great news! Singapore ETH-Centre is currently hiring and seeking a Postdoc Researcher (2 Years) T150 01201 BE FIT SEC to join their team. Feel free to download the job details.
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