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Université de Sherbrooke

PhD in Wall-Pressure Modeling for Airfoil Noise Predictions with DNS and Interpretable Deep Learning Université de Sherbrooke in Canada

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded 3-year PhD scholarship with a doctoral stipend of CAD 2,300 per month. Full-time position (35 hours/week).

Deadline

Jan 1, 2027

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Country

Canada

University

Université de Sherbrooke

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Keywords

Computer Science
Aerodynamics
Mechanical Engineering
Deep Learning
Aerospace Engineering
Mathematics
Python Programming
Physics
ML

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About this position

PhD opportunity in computational aeroacoustics, CFD, and interpretable deep learning at the Université de Sherbrooke in Canada, with collaboration from ISAE-Supaero in France.

The project focuses on wall-pressure modeling for airfoil noise predictions using direct numerical simulations (DNS), large-eddy simulations (LES), and machine learning. The research aims to improve prediction of wall-pressure spectra for broadband trailing-edge noise by extending training databases, incorporating non-equilibrium boundary-layer effects, and identifying optimal inputs for robust models across flow regimes.

This is a fully funded 3-year PhD in the Department of Mechanical Engineering, based in Sherbrooke, Quebec, Canada. Funding includes a CAD 2,300/month doctoral scholarship and a full-time workload of 35 hours per week.

Research keywords: computational aeroacoustics, airfoil noise, wall-pressure fluctuations, CFD, LES/DNS, deep learning, interpretable ML, aerodynamics, Python.

Eligibility highlights: master’s degree or equivalent in aerospace or mechanical engineering; strong background in aerodynamics, CFD, and Python; ML framework experience (PyTorch, TensorFlow, JAX) is an asset; French is also an asset.

Supervision: Prof. Antonio Alguacil Cabrerizo, Prof. Stéphane Moreau, and Prof. Michaël Bauerheim.

How to apply: email your CV, motivation letter, and a sample of past scientific work to [email protected] as soon as possible. The ad states that international applications are welcome.

Deadline: Friday, January 1, 2027.

Funding details

Fully funded 3-year PhD scholarship with a doctoral stipend of CAD 2,300 per month. Full-time position (35 hours/week).

What's required

Applicants should have a master's degree or equivalent in aerospace or mechanical engineering. Strong skills in aerodynamics, computational fluid dynamics (CFD), and Python programming are required. Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX is a plus. Autonomy, motivation for interdisciplinary research, and knowledge of French are desirable.

How to apply

Send a CV, motivation letter, and a sample of past scientific work (such as a thesis, conference paper, or research project) by email to the contact address as soon as possible.

More information can be found here

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