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Research Assistant (H1032) at ETH SINGAPORE SEC LTD.

Research Assistant (H1032)

ETH SINGAPORE SEC LTD. Singapore Contract


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 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 stroke, as a consequence of a rapidly ageing population with mobile digital technologies, covering the value chain from acute care to patient's private homes.

Project Background

Our project within FHT aims to develop and investigate human-machine interfaces that promote sensorimotor recovery in patients with stroke. We will be researching to establish a novel paradigm for transcranial magnetic stimulation (TMS)-based neurofeedback training for complex hand movements. This paradigm will first be developed in healthy participants and will then be applied in stroke survivors with either virtual reality or a hand exoskeleton. We are looking for a Research Assistant to work with an international team of researchers and technicians from SEC, ETH Zurich, and local partners in Singapore, including the Nanyang Technological University (NTU) and Tan Tock Seng Hospital (TTSH).

Job Description

As a Research Assistant in the FHT, you will be responsible to

  • Research, design, implement, test, and manage software/hardware for the brain-computer interface driven therapy project.
  • Deliver technical project management for FHT research activities at SEC including project planning activities, engineering requirements, effort estimates, and on-site and remote exchange with several research partners.
  • Conduct research for the TMS-based neurofeedback training, including participant recruitment and scheduling, data collection, data processing, and analysis.
  • Interact with end users as well as researchers at SEC, ETH Zurich, and local partners.


This position requires:

  • A university or applied science Bachelor degree in Neuroscience, Rehabilitation Science, Psychology, Cognitive or Behavioural Science, Biomedical Engineering, or a related field with minimum 2 years work experience.
  • Experience with electrophysiological measurements, ideally electromyography (EMG) and/or TMS
  • Good “people skills” when interacting with participants, patients, and colleagues
  • Interested in working with and developing new technologies for upper limb rehabilitation following a stroke

The following competencies will be advantageous:

  • Programming skills in MATLAB, Python, or a similar programming language
  • Can present technical complex aspects in a concise and easy-to-understand way
  • Be proactive, communicative and show personal responsibility, initiative and enjoy technology and interdisciplinary teamwork
  • Can work autonomously and with a self-starter attitude
  • Good communication skills orally and in writing
  • Previous experience with health-related data

We look forward to receiving your online application with the following documents

  • Cover letter outlining your motivation and experience in the field
  • A comprehensive CV including certificates (e.g. Master's and/or Bachelor's degree)
  • Transcript of records

Applications via email or postal services will not be considered.

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.


Recommended Skills

  • Behavioural Science
  • Biomedical Engineering
  • Communication
  • Data Collection
  • Data Processing
  • Electrophysiology
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