Full Time Staff Scientist

1 day ago


Old Toronto, Canada University of Toronto Full time
p>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 $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. p>

This posted position is for a Staff Scientist within the AI and Automation Lab.

  • 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: p>

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.

  • 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 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.
    • 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.
    • Support research-focused events such as Annual Symposium.


  • Old Toronto, Canada University Of Toronto Full time

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