Queen's University Fully Funded PhD in Legal AI, LLMs and NLP
Queen's University
Queen's University is offering a fully funded PhD position beginning January 2027 in artificial intelligence for law, legal applications of large language models, natural language processing and machine learning. The student will be co-supervised by Professors Xiaodan Zhu and Samuel Dahan.
Queen's University in Kingston, Canada, is recruiting a fully funded Ph.D. student to begin in January 2027 and work at the intersection of artificial intelligence, law and society.
The research will cover artificial intelligence for law, large language models for legal applications, natural language processing and machine learning. The student will be co-supervised by Professor Xiaodan Zhu, who leads the Text Analytics and Machine Learning group, and Professor Samuel Dahan, Director of the Conflict Analytics Lab.
The successful student will also participate in the Vector Institute community through talks, events, tutorials and meetings and will have access to advanced GPU and computing-cluster resources.
Funding: the recruitment announcement explicitly states that the position is fully funded. Queen's guarantees a minimum annual funding package for eligible full-time Ph.D. students who request financial support in their admission application; the published 2026–27 minimum is CAD 25,000. The applicant's offer letter controls the exact amount, sources, duration, tuition treatment and conditions.
Application route: complete the dedicated Google form, then email Professor Xiaodan Zhu with a CV and transcripts as directed by the form. Because this opening is for a Ph.D., applicants should select the Ph.D. route and disregard the form's thesis-based Master's option.
Benefits
- One fully funded Ph.D. position beginning in January 2027.
- Co-supervision by Professors Xiaodan Zhu and Samuel Dahan.
- Research affiliation with the Text Analytics and Machine Learning Group and Conflict Analytics Lab.
- Participation in Vector Institute talks, events, tutorials and research meetings.
- Access to advanced GPU and computing-cluster resources.
Eligibility summary
- Applicants should normally hold or complete a relevant Master's degree before the January 2027 start.
- Rare direct-entry exceptions may be considered for bachelor's graduates with an unusually strong publication record.
- Relevant backgrounds include computer science, computer engineering, artificial intelligence, machine learning, natural language processing, data science or closely related fields.
- Strong interest in legal AI, LLMs for legal applications and responsible work at the intersection of computing, law and society.
- Applicants must meet Queen's graduate admission and English-language requirements.
Requirements
- Complete the dedicated academic-background form.
- Select the Ph.D. option in the form.
- Provide degree institutions, fields, dates, GPAs, publication record and English-test information where applicable.
- Email the CV and transcripts to Professor Xiaodan Zhu after completing the form.
- Complete Queen's formal graduate admission process if selected.
Documents required
- Publicly accessible CV in PDF format, including GPA for each degree.
- Transcripts for all completed and current degrees.
- Summary of accepted publications and papers under review or in preparation.
- English-language test score or explanation of exemption or pending score.
- Any additional materials required for formal Queen's admission.
Language/test requirements
How to submit applications
Provider: Text Analytics and Machine Learning Group, Queen's University
Application form: https://docs.google.com/forms/d/e/1FAIpQLScrx0USu6KinqTtJmJWiG-uErPPiNQsemZ43nGLQxC-0LnfCQ/viewform Faculty profile: https://ingenuitylabs.queensu.ca/people/xiaodan-zhu Funding packages: https://www.queensu.ca/grad-postdoc/grad-studies/funding/packages Programme: https://www.queensu.ca/academic-calendar/graduate-studies/programs-study/electrical-computer-engineering/electrical-computer-engineering-phd/
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