Staff Scientist

Staff Scientist

Date Posted : 03 / 20 / 2024

Req ID : 30501

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 infield 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 $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 :

Inorganic solid-state materials,

Organic small molecules for advanced materials,

Drug discovery with chemical probes,

Polymers for materials science and biological applications,

Formulations for pharmaceuticals, consumer products, and coatings,

Biocompatibility (organ-on-a-chip), and

Synthetic scale-up of materials and molecules.

We are hiring staff scientists to develop the hardware and software needs for each of these SDLs and to conduct research programs levering these labs for materials and molecule discovery.

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.

This role will report to the Academic Director and Executive Director of the Acceleration Consortium. We are looking for individuals with diverse backgrounds and expertise to support the development of Self-Driving Labs and materials discovery.

The Staff Scientists will work with a diverse team of leading experts at the U of T, including : Alàn Aspuru-Guzik, Christine Allen, Cheryl Arrowsmith, Frank Gu, Jason Hattrick-Simpers, Anatole von Lilienfeld, Milica Radisic, Sophie Rousseaux, Florian Shkurti, Dwight Seferos, Dave Sinton, and Helen Tran.

The background of the team hired will cover the following topics. Candidates that have experience in several or as many of the areas below will be prioritized :

Artificial Intelligence / Automation

Machine Learning for Molecules and Materials

Physical, theoretical and / or computational chemistry

Robotics

Experimental planning and design / optimal control

Programming and high-performance computing

Cheminformatics

Automated Chemical Synthesis and Characterization

High-throughput materials synthesis and processing (polymers, inorganic and organic molecules (including lipids))

Nanomaterial synthesis and characterization

Polymer physics

Structural, electrochemical, and microstructural characterization of materials and molecules

Screening electrocatalytic conversion

Analytical chemistry and separation method development

Chemical reactions and analytics

GLP formulation skills

Electrochemistry

Organic synthesis methodology development

Drug Discovery / Medicinal Chemistry

Medicinal chemistry

Protein biophysics / biochemistry

Mass spectrometry

Controlled release properties and processes

Organ on a chip / Organoid

Pluripotent stem cell differentiation

Molecular biology

Toxicology pharmacology

The components and duties of the work 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 Physical / Material Chemistry or related discipline

Experience

Five (5) to 10 years of experience in research and development, preferably with significant experience in Physical, Material, Medicinal, and / or Analytical Artificial Intelligence for Chemistry.

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

Demonstrated track record of academic and / or research excellence.

Skills

Strong in communicating effectively and efficiently 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.

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

Employee Group : Research Associate

Appointment Type : Grant - Continuing

Schedule : Full-Time

Pay Scale Group & Hiring Zone : A maximum salary of $150,000 (salary will be assessed based on skills and experience)

Job Category : Research Administration & Teaching

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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 [email protected] .

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