Postdoctoral Scholar
University of Alberta View all jobs
- Edmonton, AB
- Permanent
- Full-time
- Develop ML Frameworks: Design and train deep learning architectures, such as Physics-Informed Neural Networks (PINNs) and CNNs, to model complex fluid flow and transport phenomena.
- Generate High-Fidelity Data: Utilize advanced CFD simulations or experimental data to produce high-quality datasets for training and testing surrogate models.
- Algorithm Integration: Couple machine learning models with open-source or commercial CFD solvers to accelerate convergence and reduce overall computational costs.
- Model Validation: Perform rigorous error propagation analysis and validate data-driven predictions against established experimental and numerical benchmarks.
- Disseminate Research: Author high-impact manuscripts for peer-reviewed journals and present findings at major international conferences in fluid mechanics and AI.
- Mentorship & Leadership: Provide technical guidance to graduate and undergraduate students while contributing to the collaborative growth of the research group.
- Ph.D. degree in Mechanical Engineering, Chemical Engineering, Computer Science, Physics, Applied Mathematics, or a closely related field.
- A strong record of research excellence demonstrated by first-author publications in peer-reviewed journals focusing on fluid mechanics, computational science, or machine learning.
- Demonstrated experience in developing or implementing numerical methods for Computational Fluid Dynamics (CFD).
- Advanced theoretical understanding of fluid mechanics, turbulence modeling, and transport phenomena.
- Expert proficiency in Python and core scientific computing libraries (e.g., NumPy, SciPy, Pandas).
- Hands-on experience with deep learning frameworks
- Proven ability to develop and train neural network architectures (e.g., PINNs, CNNs, or RNNs) for physical systems.
- Excellent technical writing and communication skills for manuscript preparation and international conference presentations.
- Ability to work effectively in a collaborative, multidisciplinary team environment.
- Curriculum vitae
- Cover letter
- List of publications
- Academic referral letters