Research Associate (SDL1, Two-year Term)

Job summary

The Research Associate will contribute to automated and high-throughput materials discovery by designing experimental workflows and optimizing laboratory apparatus. They will also analyze experimental datasets using AI/ML methods and document research protocols for the Acceleration Consortium's self-driving laboratories.

Job details

Date Posted: 09/18/2026Req ID: 50250Faculty/Division: Faculty of Arts & ScienceDepartment: Acceleration ConsortiumCampus: St. George (Downtown Toronto)Position 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, curriculum vitae and three reference names with their contact addresses and phone numbers. Any questions regarding this position should be directed to Sean Caffrey (sean.caffrey@utoronto.ca). All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. MINIMUM QUALIFICATIONS: PhD degree in engineering, materials science, chemistry, mechatronics, or a related field Minimum 1 year of demonstrated research experience in automated, autonomous, or high-throughput experimental systems Experience developing, integrating, or operating laboratory automation platforms for materials synthesis, characterization, or testing Hands-on experience with laboratory instrumentation and characterization techniques such as SEM, XRD, XRF, spectroscopy, photochemistry, or related analytical tools Experience in the design and optimization of photocatalytic or photothermal reactor systems for applications such as hydrogen production, CO2 conversion, or hydrocarbon dehydrogenation. Demonstrated experience in the design, synthesis, and evaluation of inorganic catalytic materials for photocatalytic, photothermal, or photoelectrochemical energy conversion. Additional skills required include project management, leadership and interpersonal skills to assist in the guidance and implementation of the research project that is comprised of a multi-disciplinary and international team of scholars. Please refer to our website ( https://people.utoronto.ca/employees/) for some general information about benefits. Closing Date: 11/30/2026, 11:59PM ETEmployee Group: Research Associate Appointment Type: Grant - Term Schedule: Full-TimePay Scale Group & Hiring Zone: R01 -- Research Associates (Limited Term): $53,520 - $100,350 Job Category: Research Administration & Teaching Lived Experience StatementCandidates who are members of Indigenous, Black, racialized and 2SLGBTQ+ communities, persons with disabilities, and other equity deserving groups are encouraged to apply, and their lived experience shall be taken into consideration as applicable to the posted position.

What you’ll do

The Research Associate will contribute to automated and high-throughput materials discovery by designing experimental workflows and optimizing laboratory apparatus. They will also analyze experimental datasets using AI/ML methods and document research protocols for the Acceleration Consortium's self-driving laboratories.

Requirements

Candidates must hold a PhD in engineering, materials science, chemistry, mechatronics, or a related field. A minimum of one year of demonstrated research experience in automated or high-throughput experimental systems is required.

Listed skills

• Technical Documentation · Preferred
• Data analysis · Preferred
• Machine learning · Preferred
• Project management · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Laboratory automation
• High-throughput experimentation
• Materials science
• Inorganic chemistry
• Data analysis
• Artificial intelligence
• Machine learning
• Robotics
• Spectroscopy
• Photochemistry
• Project management
• Technical documentation
• Experimental design
• Statistical analysis
• SEM
• XRD
• Technical Documentation
• Project Management
• Presentations
• Workflow Management
• Leadership
• Machine Learning
• Artificial Intelligence
• Data Quality
• Resilience
• Chemistry
• Research
• Interpersonal Communications
• Data Acquisition
• Data Management
• Search Engine Marketing
• Electronics
• Project Planning
• Research Experiences
• Teaching
• Research And Development
• Mechatronics
• X-Ray Fluorescence
• Materials Science
• Commercialization
• Laboratory Automation
• Laboratory Instrumentation
• Energy Conversion
• Hydrogen Production

Job areas

• Science & Research
• Engineering
• Technology
• Energy
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