Postdoctoral fellow in Biomedical or Computer Engineering

The Toronto Rehabilitation Institute is the world’s leading rehabilitation research centre. We integrate innovative patient care, ground-breaking research, and diverse education to advance the science of rehabilitation. Toronto Rehab is a member of the University Health Network and is affiliated with the University of Toronto. Toronto Rehab has state of the art research facilities for the rehabilitation sciences. It is located in downtown Toronto, a livable and cosmopolitan city known for its diversity and vibrant academic community.

At Toronto Rehab, Dr. Andrea Iaboni co-leads the Dementia Rehab group, which is part of the Walter and Maria Schroeder Institute for Brain Health and Recovery. We are working to revolutionize the care of people with dementia by organizing, integrating, analyzing, and modeling physiological and behavioural data gathered across the clinical environment using environmental and wearable sensors and the electronic medical record. This group consists of clinician scientists in the areas of geriatric psychiatry, nursing, occupational therapy, and psychology, along with engineering and data scientists.

Job Description:
You will be working with a clinician scientist and computer scientist to process and analyze sensor data for the digital phenotyping of neuropsychiatric syndromes in people with dementia. You should have an interest in the clinical neurosciences, dementia or other disorders of aging, and the development of clinical systems for improving quality and safety of care. Your responsibilities will include:
• Helping to build and maintain a sensor system in an inpatient clinical setting at Toronto Rehab
• Leading the analysis of longitudinal sensor data for the development of digital phenotypes of neuropsychiatric symptoms
Qualifications:
• PhD degree in Biomedical, Computer or Electrical Engineering
• Experience in the design of clinical sensor systems.
• Experience in data structures and engineering.
• Experience in processing large amounts of data
• Strong interpersonal, communication, organizational and collaborative abilities.
• Experience in collaboration between research and clinical groups.
• Excellent academic writing skills
Desired:
• Machine learning expertise
• Previous interest in technology in dementia and aging
• Experience in statistical models for intensive longitudinal data analysis