Research Fellow, Power Systems with Machine Learning Background

4 days left

04 Nov 2020
End of advertisement period
04 Dec 2020
Contract Type
Full Time

A Research Fellow position is available in the School of Electrical & Electronic Engineering.

Job Responsibilities

  • Conduct the research on development in partial discharge (PD) and faults detection and their associated identification algorithms using machine learning techniques to ensure PD and/or faults can be detected timely and cleared or avoided for continuity of electricity supply without interruption and for the proper management of the electrical power network
  • Introduce novel machine learning algorithms and develop methodologies for the implementation of PD/fault detection and identification

Job Requirements

  • PhD in Electrical and Electronic Engineering, Power Engineering, Computer Science, or related field, with strong background in machine learning
  • Knowledge in power systems is a must
  • Proficiency in AI programming languages such as Python or MATLAB
  • Excellent verbal communication and written skills in English
  • Hardware experience and exposure to components of power substation will aid in the project execution
  • Strong analytical and conceptual abilities
  • Able to work independently and in a team to realize the proposed works
  • Able to publish conference/journal papers
  • Able to commit your time in the project

We regret only shortlisted candidates will be notified.

Hiring Institution: NTU

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