Research Associate

Responsibilities

• Design, execute, and optimize research experiments related to advanced formulations and materials development
• Develop and implement automated and high-throughput experimental workflows
• Support staff scientists in integrating machine learning, data-driven optimization, and autonomous experimentation strategies
• Analyze, curate, and interpret experimental data to extract insights into material performance and stability
• Coordinate laboratory operations, including equipment maintenance, inventory management, and procurement
• Mentor and train graduate and undergraduate researchers on laboratory methods and SDL technologies
• Contribute to grant applications, scientific publications, technical reports, and presentations

Requirements

• Ph.D. in Chemical Engineering, Materials Science, Pharmaceutical Sciences, Physical Chemistry, Mechanical Engineering, Mechatronics, or a related discipline
• Minimum 1 year of research experience in automated, autonomous, or high-throughput experimental systems
• Demonstrated wet lab experience in soft materials or formulation development (e.g., drug delivery, colloids, rheological characterization)
• Experience with laboratory automation, robotics, or high-throughput experimentation
• Proficiency in scientific programming using Python or related languages
• Experience applying data analysis, statistical methods, or machine learning to experimental research

About the Company

The Acceleration Consortium (AC) at the University of Toronto is a global community of academia, industry, and government leveraging AI, robotics, and materials science to create self-driving laboratories. Supported by a $200M Canadian First Research Excellence Grant, the AC aims to accelerate the design of materials and molecules for a sustainable and resilient future.