Staff Research Scientist (Term 2 year, Inorganic Lab)

Date Posted: 03/20/2024
Req ID: 35046
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 received a 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. These include:

  1. Inorganic solid-state materials,
  2. Organic small molecules for advanced materials,
  3. Drug discovery with chemical probes,
  4. Polymers for materials science and biological applications,
  5. Formulations for pharmaceuticals, consumer products, and coatings,
  6. Biocompatibility (organ-on-a-chip), and
  7. Synthetic scale-up of materials and molecules.

 

 

This posted position is for a Staff Research Scientist within SDL1: Inorganic

 

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

  

Inorganic materials expertise

  • High-throughput inorganic materials synthesis and processing
  • Structural, electrochemical, and/or (opto) electrical characterization of inorganic materials
  • Physical, theoretical and/or computational inorganic materials chemistry and physics
  • Applied inorganic materials expertise in one or more of: energy storage and conversion, electrochemical systems, catalysis, optoelectronics, corrosion-resistance, high temperature structural stability, and more.

 

Artificial intelligence / automation expertise

  • Machine learning in inorganic materials science
  • Robotics and automation
  • Experimental planning and design/optimization
  • Programming and high-performance computing
  • Materials informatics

 

The Staff Research Scientists will work with a diverse team of leading experts at U of T, including Professors David Sinton, Jason Hattrick-Simpers, Yu Zou, and more. 

 

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:

 

1. 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.

 

2. 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 planning 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 the preparation and submission of research proposals to granting agencies and progress reporting.
  • Preparing manuscripts for submission to peer-reviewed publications/journals and stewarding them through the process.

3. Other

  • Supporting consulting services related to the application of SDLs for materials discovery for the AC’s partners.
  • Support research-focused events such as the Annual Symposium

 

MINIMUM QUALIFICATIONS:

 

Education – Ph.D. in Physics.

 

Experience

  • 1 to 3 years of experience in combining machine learning and high-throughput first principles calculations to accelerate discovery.
  • Experience working with industry partners and on industry lead research and development projects.
  • Expert knowledge of AI and automation and experience with the development of self-driving laboratories.
  • Experience presenting research at academic conferences. 
  • Experienced in AI for materials science: python packages, tree-based models & graph neural networks, active learning, model interpretability & dimension reduction techniques.
  • Experienced user of High-Performance Computing (HPC) Linux clusters.

 

Skills

  • Strong and effective communicator in oral and written English
  • Collegial in working with team members and collaborators.
  • Ability to work independently. 
  • Scientific software: VASP, LAMMPS, Thermo-Calc (CALPHAD), Phonopy, Origin.
  • Programming languages: Python, Fortran, Bash, Matlab, C, LaTeX.

 

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: 07/01/2024, 11:59PM ET
Employee Group: Research Associate
Appointment Type: Grant - Term
Schedule:
Pay Scale Group & Hiring Zone: R01 -- Research Associates (Limited Term): $51,543 - $96,643 Salary will be assessed and may go above the range based on skills and experience. 

Job Category: Research Administration & Teaching

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

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.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.

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.

If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca.


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