Staff Research Scientist (AI for Self-Driving Labs, 2-year Term)

University of Toronto; Toronto; On-site; CAD 56,000 - 104,000; Full time

Benefits offered by this job

Grant-funded

Collaborative environment

Job summary

The University of Toronto's Acceleration Consortium invites applications for a Staff Research Scientist within SDL0: AI & Automation. You will develop AI-driven autonomous laboratories, design experimental workflows, and collaborate with world-leading researchers to advance materials discovery.

You will lead hardware and software development for SDLs, manage research programs, publish results, and secure ongoing partnerships with industry and government.

Qualifications

• PhD in Computational Chemistry, Software Engineering, Physics, Chemistry, Materials Science, Biology, or equivalent.
• Experience in AI for self-driving labs and automation.
• Strong publication record and ability to lead research projects.

Responsibilities

• Develop SDL plans and instrument designs for AI-driven automation.
• Create hardware and Python software to build SDLs and manage procurement.
• Lead research programs leveraging SDLs to accelerate discovery.
• Prepare manuscripts and engage with grant proposals and progress reporting.

Skills

Python

LaTeX

Git

MS Office

Education

PhD in a relevant field

Job description

Date Posted: 10/19/2026
Req ID: 50600
Faculty/Division: Faculty of Arts & Science
Department: Acceleration Consortium
Campus: St. George (Downtown Toronto)

Description

The Acceleration Consortium (AC), based at the University of Toronto (U of T), is a global community of academia, industry, and government working to accelerate the discovery and development of advanced materials and molecules. The AC develops self-driving laboratories (SDLs), autonomous research platforms that integrate artificial intelligence, robotics, automation, and advanced computing to dramatically reduce the time and cost of scientific discovery. AC Staff Research Scientists are highly skilled, experienced, and independent researchers that develop the AI and automation technologies required to build robust and scalable self-driving labs, manage these SDLs, and design and implement collaborative research programs that leverage the SDLs to accelerate discovery. Staff Scientists will advance SDL technologies and apply them to challenges in areas such as clean energy, sustainability, healthcare, and advanced manufacturing. The Acceleration Consortium (AC) promotes 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.

SDLs Core Facilities

SDL0 - A central AI and automation lab to advance the robotics and AI tools used in SDLs
SDL1 - Inorganic solid-state materials 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 - Human organ mimicry with organoids / organ-on-a-chip
SDL7 - Synthetic scale-up of materials and molecules (University of British Colombia partner lab)

Posted Position

This posted position is for a role within SDL0: AI & Automation.

Desired Experience

Experience in one or more of the following is desired:
Close collaboration with experimental scientists, achieving scientific objectives with AI-driven systems.
Agentic and sequential decision-making for autonomous experimentation, including active learning and optimal experimental design.
Generative and probabilistic modeling, including uncertainty estimation, risk-aware prediction, and data-efficient learning.
Applied machine learning on real-world experimental or industrial data, including multivariate time-series and noisy, sparse, or incomplete datasets.
Orchestration and control of self-driving laboratories, including experimental workflow automation, instrument integration, and real-time data processing.

Staff Research Scientists will work with a diverse team of leading experts at U of T, including Faculty and Staff Scientists in and associated with SDL0 such as: Alán Aspuru-Guzik, Anatole von Lilienfeld, Kourosh Darvish, Florian Shkurti, Chris Sutton, Willi Gottstein, and more. Moreover, the Staff Scientists will work collectively, sharing knowledge among each other (spanning all AC labs), local and global AC faculty, and the many trainees that work in these labs. This role will report to the Academic Director and Executive Director of the Acceleration Consortium.

Components and Duties of the Work

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 the plans for SDLs that will meet user requirements and designing novel instruments for automated material synthesis and characterization. Developing customized hardware and Python software packages to build SDLs. Selection, procurement, and installation of the equipment required for SDLs.

Research Direction

Working with the AC community, develop research programs that leverage the AC’s SDLs and support 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

Implementing 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

Other

Supporting 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 Computational Chemistry, Software Engineering, Physics, Chemistry, Materials Science, Biology, or equivalent.

Experience

1 to 5 years of experience (inclusive of PhD and/or post-graduate work) in research and development, preferably with significant experience in AI for self-driving labs.
Experience in AI for science.
Experience in the development of AI tools for self-driving labs.
Experience 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 AI utilization in experimental planning, and workflow establishment for seamless integration of experiments and simulations.
Strong experience and expert knowledge of AI and automation.
Experience 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

Expert Skills: Python, LATEX, Git, Microsoft Office.
Strong and effective communicator in oral and written English.
Collegial in working with team members and collaborators.
Ability to work independently.

Other

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

Employee Group

Research Associate

Appointment Type

Grant - Term

Schedule

Full-Time

Pay Scale Group & Hiring Zone

R01 -- Research Associates (Limited Term): $55,661 - $104,364, salary will be assessed based on skills and experience

Job Category

Research Administration & Teaching

Closing Date

11/21/2026, 11:59PM ET

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 [e-mail].

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