Acoustic Data Science Engineer (probes) / Ingénieur En Data Science Acoustique (probes)

GE HealthCare UK

Valbonne, France
Machine learning methods
Ultrasound transducer design
Predictive performance monitoring
This position concerns the application of machine learning (ML) methods to the ultrasound transducer design, development, and manufacturing process

Job Summary

  • This position concerns the application of machine learning (ML) methods to the ultrasound transducer design, development, and manufacturing process.
  • The successful candidate will be specifically expected to utilize their technical background to contribute and drive forward projects that will improve efficiency in design and manufacture of transducers and perform predictive performance monitoring.
  • Within a multidisciplinary team in Valbonne connected globally to colleagues throughout Europe, Asia and the USA, this position shall provide a unique opportunity to utilize ML to make a large impact in a global ultrasound business.

Matching Summary

This position concerns the application of machine learning (ML) methods to the ultrasound transducer design, development, and manufacturing process.

Skills & Requirements

Must-have

  • Machine learning methods
  • Ultrasound transducer design
  • Predictive performance monitoring
  • MATLAB and Python
  • Cloud deployment pipelines
  • Signal processing tasks

Nice-to-have

  • Work effectively autonomously
  • Work in global teams
  • Simulation-based training
  • Deep learning networks

Key Requirements

  • University degree in engineering, acoustics, physics, or applied mathematics
  • Masters or PhD preferred
  • Experience in acoustics or ultrasound measurements
  • Experience in transducer design/development
  • Strong understanding of ML methods
  • Experience applying ML to physical systems

Work Rights

Not specified

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