About The Role:

The successful candidate for this position will participate in developing state-of-the-art probabilistic and machine learning methods and tools to provide for world-class NPI and NTI and Services capabilities throughout the company. You will work in a multi-disciplinary team contributing to the applications for performing prognostics and optimizing structures and systems under uncertainty for performance, weight and cost. Applications include turbo machinery, electrical machinery, energy generation and storage devices, medical imaging equipment, and similar mechanical systems.


  • Collaborate with GE business design and services communities in the development of methods for probabilistic design, machine learning and optimization
  • Apply probabilistic design, machine learning and optimization methods to real-world industrial applications for NPI and NTI design and Services maintenance planning for GE business
  • Implement probabilistic design, machine learning and optimization methods into GE internal design

Candidate Requirements:

  • Current enrollment in PhD program, seeking technical degree in Mechanical Engineering, Electrical Engineering or a related field in an accredited college or university
  • Must be 18 years or older
Job Overview
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