Masters and Doctoral Scholarships in Machine Learning, Queen University, Canada

Expires on: 05/30/2024

Description

The Text Analytics and Machine Learning Group (TAML) at Queen’s University, led by Dr. Xiaodan Zhu, is offering fully funded PhD and Master’s positions in Natural Language Processing (NLP) and Machine Learning (ML). Join a dynamic research environment at one of Canada’s oldest and most prestigious universities, located in the picturesque city of Kingston, Ontario, with access to world-class facilities and renowned faculty.

The Text Analytics and Machine Learning Group (TAML) at Queen’s University invites applications for fully funded PhD and Master’s positions in Natural Language Processing (NLP) and Machine Learning (ML). Led by Dr. Xiaodan Zhu, the group conducts cutting-edge research in areas such as text summarization, sentiment analysis, and dialogue systems, with applications ranging from healthcare to social media analytics.

Successful candidates will have the opportunity to work on innovative research projects, collaborate with leading scholars, and contribute to the advancement of NLP and ML technologies. Affiliated with the Ingenuity Labs Research Institute, students will benefit from a supportive and collaborative research environment and gain access to state-of-the-art facilities.

Qualifications 

  •  Applicants from top universities worldwide or in Canada are welcome.
  • Strong academic background with a focus on NLP, ML, computer science, or related fields.
  •  Exceptional research potential and a passion for advancing knowledge in NLP and ML.
  •  Excellent communication and collaboration skills.
  •  Commitment to diversity and inclusivity in learning and research environments.

How to Apply

Interested candidates should submit their applications through the official Queen’s University graduate application portal: Application Link. Please ensure to include all required documents and submit your application by the deadline of May 30th, 2024. Early submissions are highly encouraged, as applications are currently under review.

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