Concordia University

What you'll study

The PhD programme centres on sustained, original research leading to a doctoral dissertation. Early in the programme students typically take a small number of advanced coursework modules to build specialised knowledge in their chosen area and to prepare for the candidacy assessment. Typical subject areas include artificial intelligence and machine learning, natural language processing, computer vision, robotics, software engineering, human–computer interaction, databases and information retrieval, distributed and cloud systems, cybersecurity, algorithms and theory, and data science.

Programme components commonly include:

• Advanced seminars and coursework tailored to the student’s research focus
• Research rotations or preliminary projects to refine dissertation topics
• A candidacy/qualifying assessment or proposal defence to confirm readiness for thesis research
• Regular supervision meetings with a primary supervisor and supervisory committee
• Publication of research in peer-reviewed conferences and journals
• A written doctoral thesis and an oral defence

Typical modules and activities

• Advanced Machine Learning and Statistical Methods
• Advanced Topics in Software Engineering
• Distributed Systems and Cloud Computing
• Research Methods and Scientific Communication
• Seminar courses featuring current research literature
• Teaching practicum or assistantship duties (where applicable)

Entry requirements

Applicants are expected to hold a relevant master’s degree (for example, an MSc in Computer Science or a closely related discipline) with a strong academic record and demonstrated research potential. Exceptional applicants with a strong bachelor’s degree and substantial research experience may sometimes be considered.

Common application elements include:

• Academic transcripts showing high standing in previous degrees
• A research statement or proposal outlining intended doctoral research
• A curriculum vitae detailing research, publications and technical skills
• Letters of reference, typically from faculty supervisors familiar with the applicant’s research
• Proof of English proficiency where applicable (e.g. TOEFL or IELTS) for applicants whose first language is not English

Admission decisions also consider availability of faculty supervision and alignment between the applicant’s research interests and faculty expertise. Funding offers, when available, are usually tied to supervisor grants, teaching assistantships or university fellowships.

Career prospects

A PhD in Computer Science prepares graduates for roles that require deep technical and research skills. Common career paths include:

• Academic positions such as postdoctoral researcher or faculty member
• Research scientist or research engineer roles in industrial R&D labs
• Senior specialist and leadership roles in machine learning, data science, software architecture and systems engineering
• Technical leadership in startups and technology firms, including roles focused on innovation, product research and prototype development
• Positions within government research institutions and policy or applied research groups

Graduates are commonly employed by universities, corporate research laboratories, technology companies in Montreal’s vibrant AI and software ecosystem, and international research centres.

Why study at Concordia University

Concordia offers a research-intensive environment within an urban, bilingual city that is a major North American hub for AI and software innovation. The university’s computer science community includes faculty with active research programmes across a broad span of subfields and a range of specialised research labs and centres. Students benefit from close supervision, interdisciplinary collaboration across engineering, design and business faculties, and access to institutional resources such as high-performance computing facilities and industry partnership networks.

Doctoral students at Concordia also benefit from structured professional development opportunities, teaching experience through assistantships, and a supportive graduate student community. The programme’s emphasis on publishing, collaboration and applied research prepares graduates to take leading roles in academia and industry worldwide.