Machine Learning for Aerospace Engineering Co-op - Spring 2025

Job Description

The group seeks a spring 2025 (approximately January through June) co-op student with an interest in applying novel machine learning techniques to solve aerospace engineering problems, for example, predicting the fluid dynamics around a vehicle. Duties could include the following: researching and implementing novel deep learning techniques, creating and running analysis models (CFD models, flight dynamics models, etc.), running of internally-developed multidisciplinary simulation software, analysis, research and development of new capabilities, and engineering design. The group seeks well rounded candidates with basic experience in software development, placing high value on teamwork, collaboration, and diversity in addition to technical skills.

Requirements

• Currently enrolled in a program of study in engineering (Preferred majors: Computer Science, Aerospace Engineering, Mechanical Engineering)
• Completed Machine Learning course
• Knowledge of Fluid Mechanics and Aerodynamics
• Experience programming in Python, Julia, or similar
• GPA 3.0/4.0 or higher

Desired

• Completed Fluid Mechanics/Aerodynamics or equivalent courses
• Experience in physics-informed machine learning to solve partial differential equations.
• Experience working from the Linux command line and parallel computing