Postdoctoral Research Fellow in Machine Learning for Mining Safety

5 days ago


Saskatoon, Saskatchewan, Canada University of Saskatchewan Full time

Job Summary:

The University of Saskatchewan is seeking a highly skilled Postdoctoral Fellow to join our research team in the Department of Mechanical Engineering. The successful candidate will be responsible for developing a machine learning algorithm to quantify the safety of underground mine roofs and sidewalls using audio recordings of tool impacts on the surface.

Key Responsibilities:

  • Develop and optimize a machine learning algorithm to predict whether an audio recording is drummy (unsafe) or tight (safe)
  • Expand the algorithm to quantify the level of drumminess and the confidence in this prediction
  • Work independently to identify, develop, and validate new ideas
  • Communicate results via publications and conference presentations

Requirements:

  • PhD in a related field within the last five years
  • Demonstrated experience in developing machine learning algorithms with small datasets of arbitrary and/or time-series data
  • Demonstrated ability to take the lead role in successfully published papers in high-quality journals or peer-reviewed conferences

Preferred Qualifications:

  • Experience with recording and processing of audio data
  • Experience with determining confidence intervals for ML classifications or regression
  • Matlab or Python programming experience

Working Environment:

The successful candidate will work in a typical office environment, with flexible hours and the possibility of working from home part-time.

Accountabilities:

  • Produce regular progress reports to the supervisor and industrial partners
  • Produce papers for publication in reputable peer-reviewed journals and conferences


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