Research Associate-2 Year Term - Artificial Intelligence and Machine Learning

Date Posted: 07/27/2022
Req ID:25786
Faculty/Division: Faculty of Arts & Science
Department: Dept of Chemistry
Campus: St. George (Downtown Toronto)



The Department of Chemistry at the University of Toronto invites applications for a Research Associate (Limited Term) for a 2-year appointment to join Professor Dwayne Miller’s Research Group. The anticipated start date is October 1, 2022. 


The Research Associate is expected to independently carry out and conduct a research project to develop Artificial Intelligence (AI) and Machine Learning (ML) algorithms for data mining in the two research streams of the group: ultrafast electron diffraction and PIRL-DIVE-MS. More details about these projects can be found at 


The candidate will take a leadership role in managing the data science project in both research streams, liaising with collaborators, and supervising post-doctoral fellows and graduate students. 

Applicants should apply online at the link below and include a covering letter, curriculum vitae and three reference names with their contact addresses and phone numbers. Any questions regarding this position should be directed to R. J. Dwayne Miller at



PhD in Physical or Structural Chemistry.


Minimum of ten (10) years of demonstrated experience in modelling and data analysis of ultrafast electron diffraction data.
Demonstrated experience in computational chemistry.
Experience with supervising graduate and post-doctoral fellows in the field of Ultrafast Electron Diffraction
Experience writing, directing, and developing research projects in the field of Ultrafast Electron Diffraction.
Experience with Lasers and optics, including non-linear optics and transient absorption spectroscopy
Expertise in Gas and solid phase Electron Diffraction research projects.

Strong knowledge of AI and ML algorithms.
Strong technical and analytical skills, a solid understanding of research methodologies, and an outstanding record of peer-reviewed publications.
Excellent communication skills, both written and oral.
Good programming skills with practical experience in MATLAB and Phyton
Proficient in Microsoft Office suite (Word, Excel, PowerPoint), and scientific visualization software (e.g., Matlab).
Excellent time management skills and organizational skills
Proven ability to mentoring 
Demonstrated ability to work with collaborating scientific partners.


Closing Date: 09/30/2022,11:59PM ET
Employee Group: Research Associate 
Appointment Type: Grant - Term 
Schedule: Full-Time
Pay Scale Group & Hiring Zone: R01 -- Research Associates (Limited Term): $47,287 - $88,663
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 is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas.

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

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.

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