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Position: Staff Research Scientist (2 years term)
Date Posted: 05/24/2024 Req 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.
Hiring is occurring on a rolling intake. Please apply ASAP and do not wait for the listed job closing date.
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 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 Research Scientist within the AI and Automation Lab.
Expertise in one or more of the following areas is desired:
AI and computational expertise Adaptive AI-driven closed-loop experimental design and analysis (such as with Bayesian optimization) AI-accelerated discovery of materials and molecules Accelerating first principles calculations of materials and molecules with AI Automation / robotics expertise High-throughput experimentation (rapid serial and/or highly-parallel experimentation) Lab automation and robotic manipulation of lab operations 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.
We are hiring both Staff Scientists and Staff Research Scientists. While Staff Scientists are expected to have 5 years of post-PhD experience, individuals with a relevant Ph.D. and associated expertise can qualify for Staff Research Scientist.
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.
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 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. Selecting, procurement, and installation of the equipment required for SDLs.
Research Direction 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 that support research collaborations and…
Toronto ON

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