Project Officer

Friday, 31 July 2020
End of advertisement period
Sunday, 30 August 2020
Contract Type
Full Time

We are looking for a Project Officer to work on a Temasek Lab funded project on innovative methods for machine learning assisted TDOA-FDOA geolocation in a noisy environment. Following are the major targets of the present project:

  • Extract sufficient statistics in noisy environments
  • Devise highly efficient ML-assisted compressive sensing algorithms suitable for the geolocation applications
  • Estimate the co-ordinates of an emitter using an ML-assisted hybrid TDOA- and FDOA-based method that are independent of structure or preamble of the data
  • Compare the performance of various ML methods with non-ML-based methods
  • Validate the developed methods using real data

Key Responsibilities

  • Conduct in-depth research on the current literature in ML-assisted geolocation and compressive sensing
  • Develop ML-based methods and algorithms to achieve at least 10x improvement in compression against the traditional methods
  • Integrate the traditional TDOA/FDOA-based geolocation approaches with ML


  • Master degree in Wireless communications, signal processing or related fields. Will also consider candidates with good Bachelors (Honours) degree and substantial relevant work experience.
  • Good experiences in one or more of the following areas: Geolocation identification algorithms, Communication system design, Wireless Communications, Compressed sensing and machine learning algorithms
  • Excellent programming skills in MATLAB, SIMULINK, C/C++, etc
  • Excellent analytical, technical and problem solving skills
  • Good publication record in reputable journals and/or conferences
  • Innovative, resourceful, and self-motivated.
  • A team player with good people skills
  • Strong verbal and written communication skills

We regret that only shortlisted candidates will be notified.

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