Date Posted: 09/18/2026Req ID: 50250Faculty/Division: Faculty of Arts & ScienceDepartment: Acceleration ConsortiumCampus: St. George Downtown TorontoPosition Number: 00055590Existing Vacancy: Yes Description: The Acceleration Consortium at the University of Toronto invites applications for a Research Associate Limited Term for a 2-year appointment. The anticipated start date is December 1st 2026. The Acceleration Consortium AC at the University of Toronto U of T is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of academia, industry, and government that leverages the power of artificial intelligence AI, robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories SDLs. These autonomous labs rapidly design materials and molecules needed for a sustainable, healthy, and resilient future, with applications ranging from renewable energy and consumer electronics to drugs. The Acceleration Consortium AC promotes an inclusive research environment and supports the EDI priorities of the unit. The Acceleration Consortium received a $200M Canadian First Research Excellence Grant for seven years to develop self-driving labs for chemistry and materials, the largest ever grant to a Canadian University. This grant will provide the Acceleration Consortium with seven years of funding to execute its vision. This posted position is for a role within the AC’s SDL1 Inorganic Materials. Supporting and under the guidance of Staff Scientists / Senior Staff Scientists, the Research Associate is expected to carry out and contribute to research projects, by way of their expertise, in the areas below. Conduct research in automated and high-throughput materials discovery, including synthesis, processing, characterization, testing, and application-driven evaluation. Design and execute high-throughput experimental workflows to investigate structure-property-performance relationships in inorganic materials. Develop, implement, and optimize automated research workflows with real-time monitoring, data acquisition, feedback, and reproducibility controls. Analyze experimental datasets using computational, statistical, and/or AI/ML methods to extract insights into material performance, stability, and process-structure-property relationships. Adapt and improve experimental platforms, testing workflows, and characterization protocols to address specific research questions and improve data quality. Designing, modifying, and fabricating custom laboratory apparatus, fixtures, and devices. Develop research protocols, data-management practices, technical documentation, and best practices for automated and high-throughput experimentation. Contribute to manuscripts, technical reports, presentations, research proposals, and collaborative project planning. Applicants should apply online at the link below and include a covering letter, curricu
