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Research Fellow, UAV Health Monitoring

Job Description

  • Develop intelligent health monitoring and fault prognosis system for UAVs. 
  • Research on related topics and publish high-quality academic papers.

Qualifications

  • A PhD degree in UAV health monitoring and fault prognosis field. 
  • Knowledge in machine learning, particle filtering, statistical inference, data analysis. 
  • Strong mathematical background is preferred. 
  • Experience in MATLAB, Python, C++ and LaTex. 
  • Excellent command of English. 
  • Knowledge of aerodynamics is a plus.

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department: Mechanical Engineering

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