The University of Toronto's Acceleration Consortium is seeking a Research Associate for a one-year term to support research initiatives in autonomous materials discovery. The role involves applying machine learning methods to experimental datasets, developing automated workflows, and collaborating with scientists to enhance materials characterization.
Responsibilities:
- 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