Senior Research Assistant, Foundation AI Scientific Materials Data

Senior Research Assistant, Foundation AI for Scientific Materials Data

Competition Number: RC99.26

Department: Applied Computer Science

Researcher: Dr. Qian Liu

Start Date: September 1, 2026

Location: Winnipeg, MB

Job Type: Term

Date Posted: July 2, 2026

Closing Date: 08/01/2026

Salary: $20.11 per hour plus 6% vacation pay

Senior Research Assistants are normally graduate students, or University of Winnipeg undergraduate students, employed to assist in the execution and evaluation of research projects in their area of study. The positions may oversee Research Assistants in areas such as the use of proper techniques, analysis, and documentation.

Senior Research Assistants work under the general supervision or direction of more senior researchers or faculty members, and are expected to exercise judgment in prioritizing, planning and organizing their own work within defined parameters.

The Senior Research Assistant will support the development of AI and machine learning methods for materials science. Responsibilities include conducting literature reviews, identifying and curating public materials datasets, implementing and evaluating machine learning and deep learning models, developing AI algorithms for materials property prediction and scientific data analysis, and assisting with manuscript and grant preparation. Potential application areas include materials property prediction, spectroscopy, materials discovery, multimodal learning, foundation models, and AI-assisted scientific knowledge extraction.

The exact research direction will be refined during the project in collaboration with the research team.

• Conduct literature reviews and summarize recent advances in artificial intelligence and materials science.
• Identify, acquire, curate, and preprocess public and research datasets relevant to materials science applications.
• Develop, implement, and evaluate machine learning, deep learning, and statistical models for materials science research.
• Design and perform computational experiments, analyze results, and interpret findings.
• Develop software, scripts, and computational pipelines for data analysis, model development, and reproducible research.
• Assist in the development of novel AI methodologies for materials property prediction, scientific data analysis, and related applications.
• Prepare technical reports, research documentation, figures, and presentations.
• Contribute to the preparation of manuscripts for peer-reviewed journals and conference publications.
• Assist in the preparation of research grant applications and progress reports.
• Collaborate with faculty members, research staff, students, and external collaborators on interdisciplinary research projects.
• Mentor and provide technical guidance to junior research assistants and undergraduate or graduate students, as appropriate.
• Participate in research meetings and contribute to project planning and implementation.
• Perform other research-related duties as assigned in support of the project objectives.

• Master’s degree in Computer Science, Data Science.
• Strong background in machine learning, deep learning, statistical modelling, or data science.
• Demonstrated ability to conduct independent research, critically evaluate scientific literature, and develop novel computational methods.
• Experience contributing to peer-reviewed publications, conference presentations, or research reports is an asset.
• Experience with scientific programming in Python, including common machine learning frameworks (e.g., PyTorch, scikit-learn).
• Experience working with large datasets, data preprocessing, and computational analysis.
• Strong written and verbal communication skills.
• Ability to work independently as well as collaboratively in an interdisciplinary research environment.

• Must be legally entitled to work in Canada.

The period of work will be from September 1, 2026 - August 31, 2027
, and the estimated total hours of work will be 1560 hours.

Note: This position is represented by the Public Service Alliance of Canada - Research Capacity Unit.

Note: The work described in this posting will be conducted in-person.

The University of Winnipeg is committed to equity, diversity and inclusion and recognizes that a diverse staff and faculty benefits and enriches the work, learning and research environments, and is essential to academic and institutional excellence. We welcome applications from all qualified individuals and encourage women, racialized persons, Indigenous persons, persons with disabilities, and 2

SLGBTQ+ persons to confidentially self-identify at time of application.

The University of Winnipeg is committed to ensuring employment opportunities are accessible for all applicants. If you require accommodation supports during the recruitment process, please contact  .

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