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Aerodynamics/Machine Learning Intern
Nashville, Tennessee, United States
About the Role
Whisper Aero is seeking a Masters level student pursuing a degree in aerospace or mechanical engineering. The purpose of this role is to develop machine learning interfaces for design/optimization of aerodynamic applications and/or prediction from compressor cascade / CFD analysis tools.
What You’ll Do
- Implement machine learning techniques to accelerate the aerodynamic design process effectively searching through high dimensional spaces and optimizing in reduced order spaces
- Research and improve current visualization processes of large data sets through automated data reduction tools
- Help with uncertainty quantification in design
- Extend AI procedures to other disciplines (structures, powertrain etc) and demonstrate efficacy in a multidisciplinary workflow
Basic Qualifications
- US Person Status
- Masters level student pursuing degrees in aerospace or mechanical engineering, data science, applied mathematics
- Familiarity with deep learning architectures like Support Vector Machines, Random Forests, Gene Expression Programming, Convolution Neural Nets, Multi-Layer Perceptrons involving supervised and unsupervised learning specifically geared for aerospace applications.
- Expertise in Python, Git, MongoDB/SQL and one of the following: TensorFlow, scikit-learn, PyTorch
Bonus Qualifications
- Compressor and or Rotorcraft Aerodynamics
- Some CFD Experience especially modeling of internal propulsor /external aerodynamic turbulent flowfields
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