Research Associate (SDL1, One-year Term)

The Acceleration Consortium at the University of Toronto is hiring a Research Associate to contribute to autonomous materials discovery using AI, robotics, and characterization tools. The role involves applying machine learning to experimental datasets, developing automated workflows, and operating characterization instruments like XPS, XRD, and SEM. This is a one-year term position within the SDL1 inorganic materials team.

• Apply machine learning methods to experimental datasets and train models for autonomous materials discovery workflows.
• Establish systematic data collection, curation, and management practices across synthesis, processing, and characterization workflows.
• Operate, maintain, and improve characterization workflows involving XPS, XRD, SEM, and related tools.
• Develop robotic and automated workflows to enable reproducible, high-throughput materials characterization.
• Work closely with scientists to advance characterization, data interpretation, and application demonstration testing across projects.
• Support the development, integration, and continuous improvement of automated inorganic materials discovery platforms.

• PhD in Materials Science and Engineering or equivalent.
• Minimum 1 year of experience in conducting research projects in inorganic and soft materials synthesis and characterization.