Postdoctoral fellowships in self-driving labs for material synthesis and characterization

Postdoctoral Researcher – Formulations Self-Driving Laboratory for Advanced Materials Development

Acceleration Consortium – University of Toronto

Faculty of the Arts and Sciences

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
unites artificial intelligence (AI), high-throughput experimentation and robotics, materials
science, chemistry, and life-sciences to create self-driving laboratories(SDLs) that accelerate
scientific discovery. 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.

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Position Summary:

We are seeking a highly motivated Postdoctoral Researcher to join our interdisciplinary team in developing and optimizing autonomous experimentation systems for advanced materials discovery. This position will be instrumental in designing, implementing, and validating self-driving laboratories (SDLs) to accelerate the development of novel heat dissipating formulations (HDFs).The successful candidate will work at the intersection of automation, machine learning, materials science and innovation in collaboration with our industrial partner. The candidate will be supervised by Dr Frantz Le Devedec, Senior Staff Scientist and co-directed by Prof. Christine Allen in the Leslie Dan Faculty of Pharmacy.

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Key Responsibilities:

• Design, develop, validate and integrate customized or commercially available autonomous     experimental equipment and modules for formulation processes and characterization including thermal and rheological properties of HDFs.

• Validate and optimize tasks of the hardware and integration in workflows (e.g., dispensing tools for challenging viscous liquids, building down-scaled reactor with high shear mixing capabilities…).
• Work on electronics, sensors, diverse motors, PCBs as well as automated platforms for real-time process monitoring.
• Collaborate with engineers and data scientists to enhance system performance and reliability.
• Train students and support the industrial collaborator on SDL operations and discoveries.
• Prepare and present to the lead staff scientist and principal investigator clear, concise materials to effectively communicate results and insights.
• Support the AC community and research-focused events such as international conferences, annual AC symposium, etc.

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Qualifications:

• Ph.D. in Physical Chemistry, Material Sciences, Chemical Engineering, Mechanical,     Electromechanical, or Mechatronics Engineering (or related field).

• Experience with experimental automation, robotics, tool development or self-driving laboratories
• Hands-on experience with formulation development and physical chemical characterization such as rheological, thermal and spectroscopic analyses.
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• Familiarity with machine learning techniques and their application to materials discovery is an asset.

• Proficiency in programming (e.g., Python, MATLAB, C++) for data analysis and automation control and module design for integration.
• Excellent problem-solving skills, teamwork, and the ability to work in a multidisciplinary environment.

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Skills

Strong in communicating effectively and efficiently in oral and written English.

Collegial in working with team members and collaborators.

Ability to work independently.

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Other 

Experience presenting research at academic and industrial meetings/conferences.

Must have a strong publication record.

Demonstrated success in preparing high quality manuscripts, presentations, reports, briefs.

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Closing Date: Evaluation of candidates will begin immediately and continue until filled.

Appointment Type: Contract (1-year).

Schedule: Full-Time.

Pay Scale:  $65,000 to $75,000 (salary will be assessed based on skills and experience).

Application: Interested candidates should submit a CV, a cover letter detailing their research experience and interests, and contact information for three references. Combine the items above into a single PDF file named: “givenname-familyname-SDL5-YYYY-MM-DD.pdf”. Email to Frantz Le Devedec (frantz.ledevedec@utoronto.ca),with the subject line “Formulation SDL5 HDF”.

This position offers an exciting opportunity to contribute to the future of materials discovery by leveraging cutting-edge automation and AI-driven experimentation. If you are passionate about pushing the boundaries of autonomous research, we encourage you to apply.

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 IndigenousPeoples, 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.

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