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Date Posted: 03/30/2026
Req ID: 47008
Faculty/Division: Faculty of Arts & Science
Department: Acceleration Consortium
Campus: St. George (Downtown Toronto)

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 Research 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 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.

SDLs

- SDL0 - A central AI and Automation lab to support all the SDLs
- 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 Columbia partner lab)

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

Experience Requirements

- 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
- Continual, transfer, and meta‑learning, with emphasis on sim‑to‑real and real‑to‑sim generalization
- Applied machine learning on real‑world experimental or industrial data, including multivariate time‑series and noisy, sparse, or incomplete datasets
- Close collaboration with experimental scientists,



translating scientific objectives into ML‑driven or autonomous systems

The Staff Research Scientists will work with a diverse team of leading experts at U of T, including: Professors Anatole von Lilienfeld, Florian Shkurti, Animesh Garg, Alán Aspuru‑Guzik, Oleksandr Voznyy, and more.

Duties

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 independently to 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

- 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

Other

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

Minimum Qualifications

Education

Ph.D. in Computational Chemistry 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 computational chemistry and self‑driving lab orchestration
- Experience in computational chemistry (property prediction and validation)
- Experience in development of self‑driving lab orchestration tools and their implementation
- 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 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 automation
- Experience working with industry partners and on industry‑led research and development projects
- Solid 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‑review journals

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.

Accessibility Statement

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

Closing Date: 05/31/2026, 11:59PM ET. Employee Group: Research Associate. Appointment Type: Grant – Term. Schedule: Full‑Time. Pay Scale Group & Hiring Zone: R01 – Research Associates (Limited Term): $53,520 – $100,350.

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

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📌 Staff Research Scientist (AI for Self-Driving Labs, 2-year Term) (Toronto)
🏢 Inside Higher Ed
📍 Toronto