Staff Scientist (Inorganic Lab)

Staff Scientist (Inorganic Lab)

Date Posted: 11/04/2025
Req ID: 45516
Faculty/Division: Faculty of Arts & Science
Department: Acceleration Consortium
Campus: St. George (Downtown Toronto)

Description:

Description:

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), also called materials acceleration platforms (MAPs). 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. AC Staff Scientists will advance the field of AI-driven autonomous discovery and develop the materials and molecules required to address society's largest challenges, such as climate change, water pollution, and future pandemics.

The Acceleration Consortium (AC) promotes inclusive research environment and supports the EDI priorities of the unit.

The Acceleration Consortium received a 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.

The AC is developing seven advanced SDLs. These include:

The AC is developing seven advanced SDLs plus an AI and Automation lab:

SDL1 - Inorganic solid-state compounds for advanced materials and energy

SDL2 - Organic small molecules for sustainability and health

SDL3 - Medicinal chemistry for improving small molecule drug candidates

SDL4 - Polymers for materials science and biological applications

SDL5 - Formulations for pharmaceuticals, consumer products, and coatings

SDL6 - Biocompatibility with organoids / organ-on-a-chip

SDL7 - Synthetic scale-up of materials and molecules (University of British Colombia partner lab)

A central AI and Automation lab to support all the SDLs

This posted position is for a Staff Scientist within SDL1: Inorganic

Expertise in the following areas is desired:

-Design, development, and operation of electrochemistry self-driving labs
-Deep understanding of self-driving workflows for oxygen-evolving electrocatalyst discovery
-Automated and high-throughput synthesis of metal oxide electrocatalysts
-Automated and high-throughput characterization of electrocatalysts (structure, composition, performance)

The Staff Research Scientists will work with a diverse team of leading experts at U of T, including Professors David Sinton, Jason Hattrick-Simpers, Yu Zou, and more.

The Staff Scientists involved in the AC are highly skilled and experienced researchers who will work independently to develop the AI and automation technologies required to build robust and scalable self-driving labs, manage these SDLs, and design and implement research programs (based on the direction of the AC’s scientific leadership team) that leverage the SDL platforms to discover materials and molecules. Moreover, the Staff Scientists will work collectively, sharing knowledge among each other, faculty, and trainees.

This role will report to the Academic Director and Executive Director of the Acceleration Consortium.

The components and duties of the work can include:

SDL and Automation Development

Working with the AC community, including faculty and partners, to determine the required capabilities of the SDLs to be built. Developing SDL plans to meet user requirements and designing novel instruments for automated material synthesis and characterization. Developing customized hardware and Python software packages to build SDLs. Selecting, procurement, and installation of the equipment required for SDLs.

Research Direction

Working independently to develop research programs that leverage the AC’s SDLs and supports the research objectives of AC faculty and industry partners. Using SDLs to synthesize and characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc.

Tasks include:

Managing the research and development projects of AC’s industry partners when implemented in AC labs.Developing plans supporting research collaborations and estimating financial resources required for programs and/or projects.Working with Product Managers to ensure research outcomes meet partner requirements.Promoting AC’s research capacity, including delivering presentations at conferences.Collaboration in preparing and submitting research proposals to granting agencies and progress reporting. Preparing manuscripts for submission to peer review publications/journals and stewarding them through the process.

OtherSupporting consulting services related to the application of SDLs for materials discovery for the AC’s partners.Support research-focused events such as Annual Symposium

MINIMUM QUALIFICATIONS:

Education – Ph.D. in Chemistry

Experience

Five (5) to 10 years of experience (inclusive of PhD and/or post-graduate work) in research and development, preferably with significant experience in self-driving labs for chemistry and materials scienceExperience in self-driving workflows for electrocatalysis. Experience in self-driving labs for the oxygen-evolution reactionExperience working closely with a Principal Investigator or as a Principal Investigator or as Project Director with responsibilities of managing, developing and executing a major research project in the area of AI and automation, including hardware integration for automation, high throughput experimentation for dataset generation, AI utilization in experimental planning, and workflow establishment for seamless integration of experiments and simulations.Strong experience and expert knowledge of AI and automationExperience working with industry partners and on industry led research and development projects.Strong experience presenting research at academic conferences.Demonstrated record of academic and/or research excellence.

Skills

Strong and effective communicator in oral and written EnglishCollegial in working with team members and collaborators.Ability to work independently.

Other

Must have a strong publication recordDemonstrated success in writing and preparing manuscripts, presentations, reports, briefs, and scientific abstracts and manuscripts for peer-reviewed journals.

All qualified candidates are encouraged to apply; however Canadians and permanent residents will be given priority

Please refer to our website ( https://people.utoronto.ca/employees/) for some general information about benefits.

Closing Date: 03/31/2026, 11:59PM ET
Employee Group: Research Associate
Appointment Type: Grant - Continuing
Schedule: Full-Time
Pay Scale Group & Hiring Zone: $62,617.00 - $150,000(salary will be assessed based on skills and experience)

Job Category: Research Administration & Teaching

.buttontext00b26598368a4abe a{ border: 1px solid transparent; } .buttontext00b26598368a4abe a:focus{ border: 1px dashed #25355a !important; outline: none !important; }

Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca.

Job Segment: Chemistry, Research Scientist, Scientific, Sustainability, R&D, Science, Engineering, Energy, Research