MSc/MASc Positions in Computer Science, Software Engineering, and Electrical and Computer Engineering in AI, Cybersecurity, and AIOps at Ontario Tech University Ontario Tech University in United States

Ontario Tech University in Canada is advertising MSc/MASc research positions for 2026 or 2027 in Computer Science, Software Engineering, and Electrical and Computer Engineering.

The supervisors named in the post are Dr. Kundi Yao and Dr. Li Yang. Their research interests align strongly with AI/ML, cybersecurity, log management and log analysis, software engineering, AIOps, large language models (LLMs), and agentic AI. Dr. Yao’s homepage also highlights software log analytics, performance engineering, software testing, empirical software engineering, and mining software repositories. Dr. Yang’s page emphasizes machine learning, deep learning, AutoML, TinyML, model optimization, cybersecurity, intrusion detection, anomaly detection, network data analytics, network automation for 6G, IoT, concept drift, continual learning, and adversarial machine learning.

This is a student recruitment post rather than a scholarship announcement. No stipend, tuition coverage, or other funding details are provided in the post, so applicants should treat the opportunity as a research-based graduate opening and confirm funding details directly with the supervisors if needed.

Eligibility is described broadly: applicants should be interested in the listed research areas and have strong backgrounds in AI and cybersecurity. Dr. Yao’s site specifically says he is looking for self-motivated Master students and asks interested candidates to email a CV and transcript, while the LinkedIn post directs applicants to a Google Form and states that applications by email are not accepted. The post also notes that the positions are in Canada and that the start date is in 2026 or 2027.

To apply, use the Google Form linked in the post and follow the instructions carefully. Do not send applications by email. If you are considering the opportunity, review the supervisors’ homepages to match your background with their research themes before submitting.