PhD Scholarship – BCI Technologies

Iverson Health Innovation Institute

• Brain-computer interface (BCI) Technologies

• 3 year SUPRA scholarship, Hawthorn location

About the scholarship
The Iverson Health Innovation Institute at Swinburne was established in 2017 to produce high quality and high impact research focused on delivering innovative technology-assisted outcomes to minimise the impact of chronic disease on patients, the health care system and society. The institute aims to improve diagnosis, treatment and outcomes, enhance quality of life and develop health care efficiencies. The focus is broad and includes investigations in mental health, acute and chronic disease, developmental and degenerative conditions, ageing and disability.

A PhD scholarship (3-year duration) is available to support research into the individual-specific brain dynamics during a motor task. The position is funded based on the condition for SUPRA-award http://www.swinburne.edu.au/media/swinburneeduau/research/docs/pdfs/scholarships/SUPRA-conditions-of-award.pdf.

The field of brain-computer interface (BCI) technologies is growing rapidly. New decoding algorithms have been described that use neuronal signals to control a robotic arm, a wheelchair or a cursor on a screen, and the potential for this technology to ameliorate neurological deficit is considerable. However, few people around the world currently use a BCI on a daily basis. The technology is limited by the existing hardware and to a greater extent by limitations in our understanding of the optimum aspects of brain signals available for decoding to interface with the neuroprostheses. A better understanding of the individual-specific brain dynamics and how to decode neural activity is central to the development of new BCI technologies. The aim of the project is to study the information transfer between brain areas and brain connectivity during motor tasks. The project involves collecting and analysing magnetoencephalography (MEG) data from humans. The project would suit someone with an interest in gaining experience in signal processing of biological data. The student should have strong analytical skills and should also have an interest in working in a multidisciplinary environment

Skills and experience
To be successful in this role you will need to demonstrate the following:

• A Bachelor degree Honours and/or a research Master’s degree in a discipline relevant to the research topic

• A background either in engineering, physics, mathematics or similar field

• Knowledge and experience with working with human participants

A full list of the selection criteria is available within the position description

Further information, contacts and support
To start an application click on begin at the bottom of this page and submit a resume, cover letter and response to the Key Selection Criteria, as listed in the Position Description below.

Please do not email or send paper applications, all applications must be submitted online.

For further information about the position, please contact Dr Tatiana Kameneva (Senior Lecturer and Vice-Chancellor’s Women in STEM Fellow) via tkameneva@swin.edu.au.

If you are experiencing technical difficulties with your application, please contact the Recruitment team on staffrecruitment@swin.edu.au

Applications close at 5pm on Tuesday 6th November 2018 (Please note we may contact candidates prior to this date).