Canadian University Offers Fully-Funded Master’s and PhD Opportunities in AI Research

Queen's University in Canada is offering funded Master's and PhD research opportunities in Artificial Intelligence (AI), Machine Learning, and Computational Materials Science, providing international students with opportunities to pursue advanced research at one of Canada's leading public universities.

Key points

• For the 2026-27 academic year, eligible full-time PhD students receive a minimum annual funding package of CAD 25, 000, subject to university requirements and satisfactory academic progress.
• For the AI and Machine Learning opportunities, applicants should possess a degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related discipline.
• Simon Fraser University Offers Fully Funded Master's and PhD Research Opportunities in Canada.
• Candidates interested in AI-Enabled Atomistic Materials Modeling should contact Assistant Professor Meng Li to discuss potential Master's or PhD research opportunities, academic requirements, and funding arrangements.
• Students can explore research opportunities under Associate Professor Ali Etemad and Assistant Professor Meng Li, whose research groups focus on artificial intelligence and advanced computational engineering.

In practice, the opportunities are associated with the university's Stephen J. R. Smith Faculty of Engineering and Applied Science and cover research in multimodal AI, deep learning, atomistic materials modeling, and energy-related technologies.

Queen's University provides financial backing to eligible full-time research graduate students. Its funding policy guarantees a minimum of CAD 25, 000 annually for eligible PhD students during the 2026-27 academic year, generally for the first four years of doctoral study. UK Announces Fully Funded Master's Scholarships for Pakistani Students. Available Master's and PhD Research Opportunities.

In practice, the research opportunities cover two major areas and are intended for students interested in artificial intelligence, engineering, and computational science. Research Opportunity Study Level Supervisor. Artificial Intelligence and Machine Learning PhD Associate Professor Ali Etemad. AI-Enabled Atomistic Materials Modeling PhD Assistant Professor Meng Li. AI-Enabled Atomistic Materials Modeling Master's (MASc) Assistant Professor Meng Li. Scholarship Benefits and Financial Backing.

Queen's University offers financial backing to eligible research graduate students through funding packages that may include scholarships, research fellowships, teaching assistantships, and research assistantships.

While research Master's students may receive financial backing during the standard duration of their programs, doctoral funding generally covers the first four years of study.

For context, the research opportunities additionally provide access to advanced research facilities, academic supervision, multidisciplinary collaboration, and opportunities to contribute to scientific publications.

Candidates must meet the academic and research requirements of their selected graduate program.

They should demonstrate a solid understanding of machine learning and deep learning, along with programming experience in Python and machine learning frameworks such as TensorFlow or PyTorch.

Relevant research experience, publications, problem-solving skills, and the ability to work independently and collaboratively are additionally notable.

For AI-Enabled Atomistic Materials Modeling, applicants should have an academic background relevant to computational materials science, engineering, physics, chemistry, or a related research discipline.

Experience in computational modeling, machine learning, molecular dynamics, or atomistic simulations may strengthen an application.

In practice, the materials research opportunity does not specify a universal minimum GPA or a separate list of mandatory technical skills. Candidates must confirm the applicable requirements with the supervisor and graduate department. English Language Test Minimum Score. IELTS Academic Overall 7.0. PTE Academic Overall 65. Duolingo English Test Overall 130. Cambridge English Assessment 185. Documents Required for Application.

Students seeking admission to the research programs should prepare their academic documents before contacting potential supervisors or submitting a university application.

Queen's University generally requires academic transcripts and recommendation letters for research graduate admissions.

Applicants may additionally need to provide degree certificates, a current academic CV, a statement of research interests, English-language test results, and other documents requested by their graduate department.

Although individual departments may impose extra requirements, research-based graduate applications normally require two academic recommendations.

Candidates should confirm the complete document checklist for their selected program before applying.

Interested candidates should first review the available research opportunities through the official Smith Engineering graduate positions page.

Applicants interested in Artificial Intelligence and Machine Learning should review Associate Professor Ali Etemad's research profile and contact his research group to confirm whether the PhD position remains available.

After identifying a suitable supervisor and confirming the availability of a position, applicants should follow Queen's University's formal graduate admission procedure.

Notably, the university's application system generally requires academic transcripts, recommendation letters, and any extra documents requested by the relevant graduate program.

Find out more details regarding the Graduate Assistantship in AI and Machine Learning (PhD), Graduate Assistantship in AI-Enabled Atomistic Materials Modeling (PhD), and Graduate Assistantship in AI-Enabled Atomistic Materials Modeling (Master's).

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Taken together, the developments around canadian University Offers Fully-Funded Master's and PhD Opportunities in AI Research point to a situation that is still moving, and the coming days should bring more clarity.