Multiple positions for graduate students are available:
The Aerospace Structures and Materials Engineering Laboratory (ASME-Lab) at 杏吧原创 University invites applications for multiple fully funded positions in advanced research on multiscale structural mechanics, multiphysics simulation, and data-driven design methodologies, with applications to aerospace structures and high-performance engineering systems.
Start Date: September 2026 (Fall intake)
Open Positions
PhD Students (4 Positions)
- PhD 1 鈥� Multiscale Fatigue and Fracture Modeling
Development of high-fidelity, physics-based frameworks linking manufacturing-induced features, microstructural architecture, and fatigue behavior in advanced and architected materials. - PhD 2 鈥� Data-Driven Modeling and Model Reduction
Formulation of computationally efficient predictive models through reduced-order modeling and physics-informed machine learning for accelerated simulation and design-space exploration. - PhD 3 鈥� Multiphysics Simulation (CFD鈥揊SI鈥揟hermal鈥揂coustic)
High-fidelity numerical investigation of coupled fluid鈥搒tructure鈥搕hermal interactions, including flow-induced vibration, aeroacoustic response, and heat transfer phenomena. - PhD 4 鈥� Multiscale Design Optimization and Digital Twins
Development of integrated, multi-objective optimization frameworks and digital twin environments for real-time prediction, uncertainty quantification, and design automation.
MASc Students (2 Positions)
- MASc 1 鈥� Experimental Mechanics and Fatigue Characterization
Experimental investigation of fatigue behavior using advanced measurement techniques (e.g., full-field strain mapping), coupled with microstructural and defect characterization. - MASc 2 鈥� Structural Dynamics, Acoustics, and Manufacturing Effects
Analysis of vibration and acoustic response, with emphasis on the influence of manufacturing-induced variability on structural and multiphysics performance.
MEng Student (1 Position)
- Computational Automation and Data Infrastructure
Development of automated computational workflows for geometry generation, simulation execution, and data management to support large-scale parametric studies and optimization.
Undergraduate Researchers (1鈥�2 Positions)
- Data Analysis and Scientific Visualization
Processing and interpretation of experimental and numerical data, including spectral analysis and development of visualization tools for multiphysics datasets.
Research Areas
- Multiscale mechanics and architected materials
- Fatigue and fracture of advanced materials
- Computational fluid dynamics and fluid鈥搒tructure interaction
- Aeroacoustics and thermal-fluid systems
- Machine learning and Artificial Intelligence
- Model order reduction and data-driven modeling
- Digital twins and predictive simulation
- Multiscale, multi-objective design optimization
What is Offered
- Engagement in high-impact, interdisciplinary research
- Collaboration with leading industrial and academic partners
- Access to advanced experimental and high-performance computing facilities
- Strong publication record and professional development opportunities
Requirements
- Degree in Mechanical/Aerospace Engineering or closely related discipline
- Strong background in computational and/or experimental mechanics, fluid dynamics, machine learning and Artificial Intelligence, or data-driven modeling
- Proficiency in scientific programming (e.g., Python, MATLAB) is desirable
Application
Interested candidates will have to apply to the appropriate graduate program in the department Mechanical and Aerospace Engineering.
However, for initial screening, applicants are encouraged to submit
- Curriculum Vitae
- Academic transcripts
- Brief statement of research interests
To: Professor Mostafa El Sayed
Email: Mostafa.elsayed@carleton.ca
Subject: HQP Application 鈥� [Position]
We are always interested in talking to talented students about potential graduate studies.聽 Please contact Professor Mostafa El Sayed if you think that the research themes described in this website are of interest to you.