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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. 

The primary responsibility of this role is to deliver on a research project in the area of Brain Computer Interface funded by the Ministry of Education where you will be a key member of the research team to develop a Non-Invasive Closed-loop Brain Computer Interface for Decoding and Control of Motor Imagery Kinematics.

Key Responsibilities

• Participate in and manage the research project with the Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.

• Lead the development of novel signal processing and machine learning methods for Brain Computer Interface (BCI)-based motor imagery kinematics decoding.
• BCI experiment paradigm design.
• Conducting BCI studies on healthy subjects as well as stroke patients in the hospital.
• Work together with a team of researchers and doctorate students to implement and test the BCI system, and also to evaluate the effectiveness of the system.
• Publish research findings in reputable journals and present at conferences and workshops.
• Mentor and collaborate with junior researchers and doctorate students, providing guidance and support in their research activities.
• Assist the PI in writing grant proposals and securing funding for future research projects.
• Work independently, as well as within a team, to ensure that project deliverables are met.

Job Requirements

• Ph.D. in Electrical/Electronic/Computer Engineering, with a strong research focus on Motor Imagery Brain Computer Interface.
• Minimum of one year’s postdoctoral experience is mandatory.
• Experience in the development of novel signal processing and machine learning algorithms for decoding motor imagery kinematics using Brain Computer Interface. A sound knowledge and algorithm development experience in Electroencephalography (EEG) error-related potential detection and real-time closed-loop Brain Computer Interface System development is required.  
• Proficiency in programming languages (e.g., MATLAB, C#), EEG data acquisition and Brain Computer Interface experiment paradigm design.
• Strong analytical and problem-solving skills, with the ability to critically evaluate and interpret research data.
• Excellent written and verbal communication skills, with the ability to publish research findings in top-tier journals and present papers at conferences.
• Proven track record of research publications in reputable journals and conferences. These publications must be in the area of Motor imagery Brain Computer Interfaces.
• Ability to work both independently and collaboratively in a research team environment.