Carleton University
4 months ago
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Fully Funded PhD in Aerospace Structures and Materials Engineering Carleton University in Canada
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD research opportunities for three students at Carleton University. Funding is explicitly stated as fully funded, but no stipend amount, tuition breakdown, or other financial details are provided.
Deadline
Expired
Country
Canada
University
Carleton University

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About this position
Fully funded PhD opportunities are available at Carleton University in the Department of Mechanical and Aerospace Engineering, within the Aerospace Structures and Materials Engineering Laboratory (ASME-Lab). The positions are for students interested in aerospace structures, advanced materials, multiphysics simulation, optimization, and data-driven engineering.
The research areas include Computational Fluid Dynamics (CFD), Fluid-Structure Interaction (FSI), aeroacoustics, structural modal analysis, wind tunnel testing, and numerical/experimental validation; machine learning, physics-informed machine learning, reduced-order modeling, and data-driven methods for engineering systems; and fracture mechanics, fatigue analysis, damage detection, and structural health monitoring for 3D-printed metals, composites, and hybrid materials.
Applicants should be highly motivated, autonomous, and academically strong. Required qualifications include graduation from an internationally recognized university, a minimum academic standing equivalent to CGPA 10.5/12 on Carleton's scale in the last 20 relevant courses, at least one first-author publication with the Master's supervisor in a Q1 or Q2 journal, and strong analytical, computational, experimental, and/or programming skills.
To apply, candidates should email their CV, transcripts, and a brief statement of research interests to Prof. Mostafa El Sayed at [email protected]. Only shortlisted candidates will be contacted.
Funding details
Fully funded PhD research opportunities for three students at Carleton University. Funding is explicitly stated as fully funded, but no stipend amount, tuition breakdown, or other financial details are provided.
What's required
Applicants must have graduated from an internationally recognized university, achieved an academic standing in their last 20 relevant courses equivalent to a minimum CGPA of 10.5/12 on Carleton University's grading scale, have at least one first-author publication with their Master's supervisor in a Q1 or Q2 journal, and demonstrate strong analytical, computational, experimental, and/or programming skills. Strong background in CFD, FSI, structural modal analysis, wind tunnel testing, aeroacoustic measurements, numerical/experimental validation, machine learning, physics-informed machine learning, reduced-order modeling, fracture mechanics, fatigue analysis, damage detection, or structural health monitoring is preferred.
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