Chemists. AI experts. Roboticists. Social scientists. Software engineers. And more. We’re looking for a diverse group of people to help us revolutionize scientific discovery.


We are scaling! The Acceleration Consortium received an $200M Canadian First Research Excellence Grant over seven years to develop self-driving labs for chemistry and materials, the largest ever grant to a Canadian University.

Chemists. AI experts. Roboticists. Social scientists. Software engineers. And more. We’re looking for a diverse group of people to help us revolutionize scientific discovery. Join our team to become part of a world leading hub for AI for science in Toronto.

The University of Toronto’s Acceleration Consortium (AC) is changing the way we do science by using artificial intelligence (AI) and automation to accelerate the discovery of materials and molecules. Materials, and our ability to develop them rapidly, are crucial to solving humanity’s most pressing challenges, from climate change to pandemics.  

The AC will achieve these goals by bringing together researchers and private-sector partners from around the world to design, develop and implement self-driving laboratories. Self-driving labs are transforming materials science by using AI to predict which novel materials and molecules will have the properties we need for a particular application. An AI-guided robotic lab then uses these predictions to autonomously synthesize, test and refine new molecules or materials with those desired properties. By incorporating all steps of materials development (design, synthesis and characterization) into a single autonomous platform that can run 24 hours per day, self-driving labs significantly reduce the time and cost of materials discovery.  

We are seeking:

CFREF funding will support the development of 7 scientific labs at U of T: 6 self-driving Labs (inorganic, organic, drugs discovery, polymers, formulations/pharmaceuticals, biocompatibility) and a machine learning and automation lab.  

We're currently seeking applications for more than 35 computational and experimental staff scientist positions
. These staff scientist positions are similar to those in US government labs and can publish corresponding authored papers and operate with a large degree of autonomy. These staff scientists will research and work out how to build self-driving labs to tackle some of the outstanding challenges in materials, chemistry, and bioresearch.  

The AC is led by Alàn Aspuru-Guzik and a team of world-class researchers working to advance AI-driven, autonomous materials discovery for a number of high-impact applications. The staff scientists will build the self-driving labs with the distinguished team of scientists listed below:

  1. Inorganic Self-Driving Lab (Led by professors Dave Sinton, Jae Hattrick-Simpers, and Yu Zou)

This lab will create inorganic materials for energy and structural applications, such as catalysts for renewable energy (e.g., hydrogen evolution reaction and CO2 utilization), corrosion/wear-resistant conductive alloys, eco-friendly cement, tough materials for extreme environments like turbines.

  1. Organic Self-Driving Lab for Sustainable Materials (Led by professors Alàn Aspuru-Guzik, Sophie Rousseaux)

This lab will create organic small molecules for sustainability applications, such as photovoltaics for solar energy conversion, emitters with inverted singlet-triplet gaps for more efficient organic light-emitting diodes (OLEDs) for displays, and environmentally friendly high-capacity storage batteries (e.g., electrolytes for redox flow batteries).

  1. Drug Discovery Self-Driving Lab (Led by professors Cheryl Arrowsmith and Rob Batey)

This lab will develop chemical probes and optimize them using automated medicinal chemistry. These probes will help us understand human biology and disease processes to ultimately identify and validate new drug targets.  

  1. Polymer Self-Driving Lab (Led by professors Helen Tran and Dwight Seferos)

This lab will create polymers for sustainably applications such as recyclable plastics, solid-state batteries, and flame-retardant materials, as well as health applications such as biocompatible coatings for implantable biosensors and antimicrobial surfaces.

  1. Formulations Self-Driving Lab (Led by professors Christine Allen and Frank Gu)

This lab will create formulations for a variety of application areas. These include  pharmaceuticals like mRNA vaccines for emerging infectious diseases; consumer products like cosmetics; and advanced coatings that are antibiotic or corrosive-resistant, for example.  

  1. Biocompatibility Self-Driving Lab (Led by professor Milica Radisic)

This lab will use organ-on-chip technology that contain engineered or natural miniature tissues grown inside microfluidic chips to test the biocompatibility and toxicity of drugs, molecules and materials.

  1. Machine Learning and Automation Lab (Led by professors Anatole von Lilienfeld and Florian Shkurti)

This lab will develop novel machine learning algorithms for synthesizing molecules, along with robotic tools for automated synthesis and characterization of these materials.  

To learn more, please review the complete job postings via the links above. And stay tuned for future opportunities–there will be more soon!


Acceleration Consortium

This piece was written by a member of the AC team

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