KITE at 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, 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. Our research group consists of clinician scientists in the areas of geriatric psychiatry, nursing, occupational therapy, and psychology, along with engineering and data scientists.
We are pleased to announce a position for a Postdoctoral Fellow. We are seeking outstanding candidates with a background in applied geriatric or dementia care research. This position will focus on the integration of technology into clinical decision-making and into the delivery of care in residential aged care and long-term care. You will working with the wider research team and various stakeholders to develop and evaluate clinical care algorithms that incorporate technology-based longitudinal assessments. A key project will involve comparing clinician assessments to 1) AI-driven risk predictions, and 2) to collaborative human-AI risk assessments.
• PhD degree in Psychology, Nursing, Physical Therapy, Occupational Therapy or other relevant clinical science
• Expertise in best practices in geriatric or dementia care
• Experience with knowledge translation and implementation science
• Experience in clinical research
• Strong interpersonal, communication, organizational and collaborative abilities.
• Experience in collaboration between engineering, computer science, and various community stakeholder groups.
• Statistical skills, particularly in intensive longitudinal methodology
• Experience in research in the long-term care sector
Potential candidates should email their CV, research statement, and contact details of two academic references to: [email protected]