Prospective Students
Currently Available Positions:
Students and graduates with excellent academic records and experience in machine learning/pattern recognition, the use of technology in healthcare, diagnostics and predictive analytics, biological signals, signal processing and control, human subject experimentation, design of novel medical technologies, and/or technologies for healthy & independent aging, are encouraged to apply.
My team works on a wide range of research topics from fundamental theory of machine learning and biological signal processing, to applied research and development of commercializable health technologies, to product design of novel toolkits for clinical validation, to biometrics and user authentication. Working in a team-based environment, you will be challenged and tested, but you will learn life skills and make life-long friends.
I am committed to providing a positive learning and working environment where everyone feels empowered to contribute and where all members of the team are respectful and respected as individuals. I am committed to fostering an inclusive culture and to advancing diversity to the benefit of the team, which is perhaps most profound in the research context. I firmly believe that diversity of thinking and experiences, passions and approaches lead to better ideation, innovation and a stronger learning environment. In an effort to improve gender equity in Engineering, preference will be given to female applicants.
If you are looking for an intense but rewarding research experience in a multi-disciplinary, clinic-centered research centre, please contact me with your CV and a description of why you would like to work and study in this area.
- An MSc candidate position focused on machine learning and computer vision techniques for gait, mobility and biometrics. The candidate should be an independent worker with a demontrated ability to be a team leader. The candidates will work in collaboration with various partners on a federally and provincially funded industry-partnered project to develop a novel gait-based biometric. Find more information about the project, see here.
- A Post-Doctoral Fellow position working on HD-EMG pattern recognition for prosthesis control. The candidates will work as part of an international collaboration with Université Laval, University of Oslo, and other industry and clinical partners to develop a novel prosthesis system.
Students and graduates with excellent academic records and experience in machine learning/pattern recognition, the use of technology in healthcare, diagnostics and predictive analytics, biological signals, signal processing and control, human subject experimentation, design of novel medical technologies, and/or technologies for healthy & independent aging, are encouraged to apply.
My team works on a wide range of research topics from fundamental theory of machine learning and biological signal processing, to applied research and development of commercializable health technologies, to product design of novel toolkits for clinical validation, to biometrics and user authentication. Working in a team-based environment, you will be challenged and tested, but you will learn life skills and make life-long friends.
I am committed to providing a positive learning and working environment where everyone feels empowered to contribute and where all members of the team are respectful and respected as individuals. I am committed to fostering an inclusive culture and to advancing diversity to the benefit of the team, which is perhaps most profound in the research context. I firmly believe that diversity of thinking and experiences, passions and approaches lead to better ideation, innovation and a stronger learning environment. In an effort to improve gender equity in Engineering, preference will be given to female applicants.
If you are looking for an intense but rewarding research experience in a multi-disciplinary, clinic-centered research centre, please contact me with your CV and a description of why you would like to work and study in this area.