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Postdoctoral Research Fellow, Mechanical Engineering

2 months ago


Saskatoon, Saskatchewan, Canada University of Saskatchewan Full time
Job Summary

We are seeking a highly motivated Postdoctoral Research Fellow to join our team at the University of Saskatchewan. 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
  • Collaborate with a student who is currently taking the recordings and other students working on other projects
Requirements
  • Ph.D. 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 experience with dataset feature engineering and dimensionality reduction
  • Demonstrated ability to take the lead role in successfully published papers in high-quality journals or peer-reviewed conferences
Desirable Qualifications
  • Experience with recording and processing of audio data
  • Experience with determining confidence intervals for ML classifications or regression
  • Matlab ML programming experience
  • Python ML programming experience
  • Familiarity with rock mechanics and mine operations
  • Familiarity with acoustic and vibrational wave propagation
What We Offer
  • A competitive salary and benefits package
  • The opportunity to work with a talented team of researchers and students
  • Access to state-of-the-art research facilities and equipment
  • The chance to contribute to cutting-edge research in Machine Learning and Mining