Research Scientist; AI Self-Driving Labs, Term

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

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 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.

The AC is developing seven advanced SDLs. These include:

• 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 Colombia partner lab)

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

Experience in one or more of the following is required:

• 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.

The Staff Research 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 Research 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.

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…