Machine Learning & CFD Engineer Intern

About

Dive into aerospace innovation as a Machine Learning & CFD Engineer Intern. Utilize neural networks to enhance analysis and design of combustion components in a dynamic learning environment.

In this internship, you'll explore advanced machine learning and CFD techniques, contributing to next-generation propulsion systems. Engage in literature reviews on neural networks and develop surrogate models for combustion cooling channels. Collaborate with international teams from France and Germany to bring your skills to real-world applications.

Key Responsibilities

• Conduct literature review on neural networks and AI models
• Implement Physics Nemo software for project workflows
• Create prototype surrogate model using Physics-Informed Neural Networks
• Define and compute CFD training datasets
• Evaluate hybrid model sensitivity to training data size

Requirements

• Pursuing a BAC+5 degree in relevant fields
• Knowledge of Machine Learning and CFD principles
• Programming proficiency in Python is essential
• Experience with Ansys Fluent is a plus
• Fluency in English; German knowledge advantageous

Leverage your technical skills to make a tangible impact on cutting-edge aerospace projects.