Staff Scientist (AI Lab)

Date Posted : 05 / 24 / 2024

Req ID : 37416

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 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.

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 r 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 Scientist within the AI and Automation Lab.

Expertise in one or more of the following areas is desired :

Generative modelling

Active learning, exploration, optimal experiment design, Bayesian optimization

Reinforcement and imitation learning

Safe exploration and learning

Representation learning

Learning to search, learning planning heuristics

Continual learning, transfer learning (sim-to-real, real-to-sim), meta-learning

Domain adaptation

Uncertainty quantification, reasoning under uncertainty, POMDPs

Neurosymbolic reasoning

Simulation-based inference

Multimodal foundation models

Staff 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 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 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 SDL plans to 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

Working independently to develop research programs that leverage the AC’s SDLs and supports 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.

Support research-focused events such as Annual Symposium

MINIMUM QUALIFICATIONS :

Education Ph.D. in chemistry, materials science, life sciences, physics, engineering, robotics, computer science, or related discipline

Experience

Five (5) to 10 years of experience (inclusive of PhD and / or post-graduate work) in accelerated research and development in the area of organic synthesis, organometallic catalysis, and computational

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 with overseeing the activities of a lab.

Experience working with industry partners and on industry led research and development projects.

Strong experience presenting research at academic conferences.

Demonstrated record of academic and / or research excellence

Must have a strong scholarly publication record.

Skills

Proficient in general organic synthesis skills, air and / or moisture sensitive techniques, and common analytical instrumentation.

Skills in electronic / hardware-oriented programming and machine learning

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-reviewed journals.

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

Closing Date : 07 / 31 / 2024, 11 : 59PM ET

Employee Group : Research Associate

Appointment Type : Grant - Continuing

Schedule : Full-Time

Pay Scale Group & Hiring Zone : $60,304.00 - $150,000( salary will be assessed based on skills and experience)

Job Category : Administrative / Managerial