Queen's University Opens Fully Funded AI Master's and PhD Research Positions for International Students

Queen's University in Canada is offering funded Master's and PhD research positions in artificial intelligence, machine learning and computational materials science, giving international students a chance to carry out advanced research at one of the country's leading public universities. The opportunities fall under the university's Stephen J. R. Smith Faculty of Engineering and Applied Science and cover areas including multimodal AI, deep learning, atomistic materials modelling and energy-related technologies.

Prospective students can pursue research with two faculty groups. Associate Professor Ali Etemad and Assistant Professor Meng Li lead teams focused on artificial intelligence and advanced computational engineering, and the openings are aimed at candidates with an interest in AI, engineering and computational science.

Financial support is a central feature of the programme. Queen's University guarantees a minimum of CAD 25,000 per year for eligible full-time PhD students in the 2026-27 academic year, generally for the first four years of doctoral study. Research Master's students may also receive funding for the standard length of their programmes.

Support is delivered through funding packages that can combine scholarships, research fellowships, teaching assistantships and research assistantships, subject to university requirements and satisfactory academic progress. Selected researchers also gain access to advanced facilities, academic supervision, multidisciplinary collaboration and the chance to contribute to scientific publications.

Applicants must meet the academic and research requirements of their chosen graduate programme. For the AI and machine learning positions, candidates should hold a degree in computer science, computer engineering, electrical engineering, mathematics or a related field, and should demonstrate a solid grasp of machine learning and deep learning along with programming experience in Python and frameworks such as TensorFlow or PyTorch.

The openings are likely to draw interest from students worldwide seeking affordable access to high-level AI research, as demand for artificial intelligence expertise continues to grow across industry and academia. Further details on eligibility and application procedures are available through the university's engineering faculty.