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Hina Tabassum

3 months ago

Postdoctoral Fellow / Research Associate in Applied AI and Foundation Engineering York University in Canada

Degree Level

Postdoc

Field of study

Computer Science

Funding

Multi-year interdisciplinary research position funded by the Ontario Ministry of Transportation (MTO) and an NSERC Alliance Grant. The post is for a Postdoctoral Fellow or Research Associate; no stipend amount is stated.

Country flag

Country

Canada

University

York University

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Keywords

Computer Science
Data Science
Machine Learning
Environmental Science
Electrical Engineering
Information Technology
Deep Learning
Artificial Intelligence
Natural Language Processing
Civil Engineering
Geotechnical Engineering
Foundation Engineering
Statistics

About this position

York University’s Lassonde School of Engineering is recruiting a Postdoctoral Fellow / Research Associate for an interdisciplinary project at the intersection of Applied AI, Foundation Engineering, Civil Engineering, Electrical and Computer Engineering, and Geotechnical Engineering.

The project is jointly supervised by Prof. Rashid Bashir and Prof. Hina Tabassum and is funded by the Ontario Ministry of Transportation (MTO) and an NSERC Alliance Grant. The research focuses on building an AI-driven pipeline to extract critical geotechnical information from unstructured PDF Foundation Investigation Reports using OCR, NLP, and deep learning. The successful candidate will also develop machine-learning models to predict design parameters such as bearing capacity and settlement behavior.

Applicants should hold a Ph.D. in Computer Science, Electrical and Computer Engineering, Civil Engineering (with a strong computational focus), Data Science, or a closely related field. Strong experience in machine learning and/or artificial intelligence is required, along with proficiency in Python, R, MATLAB, or equivalent tools. Familiarity with geotechnical concepts such as soil mechanics and foundation design is expected, and a strong publication record in AI/ML engineering applications is preferred. Experience with NLP and OCR is an asset. The post specifically notes that the candidate should currently be located within Canada.

The anticipated start date is August 15, 2026. To apply, send a CV, cover letter, research statement, and 2–3 academic references to both supervisors by email.

This is a strong fit for candidates interested in computer science, civil engineering, geotechnical engineering, AI/ML, and document intelligence for infrastructure applications.

Funding details

Multi-year interdisciplinary research position funded by the Ontario Ministry of Transportation (MTO) and an NSERC Alliance Grant. The post is for a Postdoctoral Fellow or Research Associate; no stipend amount is stated.

What's required

Ph.D. in Computer Science, Electrical and Computer Engineering, Civil Engineering with a strong computational focus, Data Science, or a closely related field. Strong expertise in machine learning and/or artificial intelligence applications is required, with high proficiency in Python, R, MATLAB, or equivalent. Familiarity with or willingness to learn geotechnical engineering concepts such as soil mechanics and foundation design is expected. A strong publication record in peer-reviewed journals focusing on AI/ML applications in engineering is preferred. Hands-on experience with NLP and OCR is preferred, and the candidate should currently be located within Canada.

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Professors

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University Name
Country flag

Canada

Research Interests

Geotechnical Engineering

Artificial Intelligence

Data Science

Machine Learning

Deep Learning

Prof.

University Name
Country flag

Canada

Research Interests

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