Archie Huang
1 week ago
MASc and PhD Positions in Transportation Engineering, AI, and Urban Data Analytics at Concordia University Concordia University in Canada
Degree Level
Master's, PhD
Field of study
Computer Science
Funding
Available
Country
Canada
University
Concordia University

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Where to contact
Official Email
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About this position
Dr. Archie Huang, Assistant Professor in the Department of Building, Civil and Environmental Engineering at Concordia University, Montreal, is recruiting highly motivated MASc and PhD students to join his research group in transportation engineering. The group focuses on cutting-edge research at the intersection of urban data analytics, traffic flow dynamics, and artificial intelligence (AI) applications in transportation systems.
Students will have the opportunity to work on projects involving deep learning, computer vision, data analytics, and large-scale network modeling. Research areas of interest include deep learning and visual recognition, traffic flow model inference and identification, electrification in transportation, and AI-enabled transportation applications such as traffic control and management.
Preferred qualifications for applicants include research experience in machine learning, computer vision, or data analytics; academic publications (for PhD applicants); experience with deep learning frameworks and large-scale network modeling; and the ability to work independently and take initiative in research. The position is open to students from diverse backgrounds and career stages who are passionate about advancing the frontiers of artificial intelligence and transportation systems.
To apply, prospective students should email Dr. Huang with a CV, academic transcripts, and a statement describing their academic and professional background as well as their research interests. Only shortlisted candidates will be contacted due to the high volume of inquiries. The research group is based at Concordia University, a leading institution in Canada, and offers a dynamic environment for interdisciplinary research in transportation engineering, AI, and urban analytics.
Funding details
Available
What's required
Applicants should be highly self-motivated and passionate about advancing artificial intelligence and transportation systems. Preferred qualifications include research experience in machine learning, computer vision, or data analytics; academic publications (for PhD applicants); experience with deep learning frameworks and large-scale network modeling; and the ability to work independently and take initiative. Application materials should include a CV, academic transcripts, and a statement describing academic and professional background as well as research interests.
How to apply
Email your CV, academic transcripts, and a statement of your academic and professional background and research interests to [email protected]. Only shortlisted candidates will be contacted.
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