GE Aerospace Research - Probabilistic Design Fellow Internship
- Collaborating with GE business design and services communities to drive system performance improvement through new design and operations processes guided by machine learning, probabilistic, and physics-based simulations, and experimental/field data.
- Applying machine learning and probabilistic design and optimization methods to real-world industrial applications for New Product Introduction (NPI), New Technology Introduction (NTI), design and services maintenance planning.
- Collecting, curating and analyze/processing data for knowledge extraction and actionable insights.
- Implementing machine learning, probabilistic design and optimization methods into GE internal design and services tools.
- Current enrollment in PhD program, seeking technical degree in Aerospace Engineering, Mechanical Engineering or a related field in an accredited college or university.
- Legal authorization to work in the U.S.
- Minimum GPA 3.0 / 4.0 scale
- Exceptional academic performance •
- Excellent organizational, analytical, and problem-solving skills, and thorough attention to detail
- Ability to adapt to change and willingness to be flexible in a global team environment
- Effective presentation and technical communication skills; ability to articulate technical problems in clear and simple terms
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