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

Date Posted: 03/30/2026
Req ID: 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 f or 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 partnerlab) 

 

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 activelearning 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-simgeneralization
• Applied machine learning on real-world experimental or industrial data, including multivariatetime-series and noisy, sparse, or incomplete datasets
• Close collaboration with experimental scientists, translating scientific objectives into ML-drivenor 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 whowill work independently to develop the AI and automation technologies required to build robust andscalable 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 todiscover 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.

 

The components and duties of the work include:

 

SDL and Automation Development

 

Working with the AC community, including faculty and partners to determine the requiredcapabilities of the SDLs to be built. Developing the plans for SDLs that will meet user requirementsand designing novel instruments for automated material synthesis and characterization. Developing customized hardware and Python software packages to build SDLs. Selection, procurement, andinstallation of the equipment required for SDLs.

 

Research Direction

 

Working independently to develop research programs that leverage the AC’s SDLs and supportstheresearch objectives of AC faculty and industry partners. Using SDLs to synthesize and characterizelarge quantities of candidate molecules, calibrating theoretical models with experimental data,predicting promising candidates with computational tools and machine learning algorithms, andelucidating 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 implementedin AC labs
• Developing plans supporting research collaborations and estimating financial resourcesrequired 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 andprogress 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-drivinglab 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 majorresearchproject in the area of AI and automation, including hardware integration forautomation, high throughput experimentation for dataset generation, AI utilization inexperimental planning, and workflow establishment for seamless integration of experimentsand simulations
• Strong experience and expert knowledge of AI and automation
• Experience working with industry partners and on industry led research and developmentprojects
• 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, andscientific abstracts and manuscripts for peer-reviewed journals

 

Applications are being reviewed on a rolling basis. Please apply ASAP and do not wait forthe listed job closing date.

 

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

 

Please refer to our  website  for some general information about benefits.

 

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 ,  salary will be assessed based on skills and experience
Job Category: Research Administration & Teaching

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.

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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.

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