[Machine Learning/AI] Machine Learning for Novel Gas Sensors

[Machine Learning/AI] Machine Learning for Novel Gas Sensors

Job Number: P20INT-26
This position requires processing time series data from novel gas sensors for machine learning and data analysis, and then developing algorithms to classify the sequences. Algorithms will be required to perform multi-label classification/regression, prediction and latent space analysis. You are expected to:
San Jose, CA
  • Process noisy sensor data.
  • Compare learned features vs. engineered features for time series data.
  • Implement state-of-the-art classification and regression models.

Qualifications:

  • M.S. or Ph.D. candidate computer science, or related STEM field.
  • Strong familiarity and research experience in machine learning, deep learning, and signal processing. 
  • Highly proficient in software engineering using C++ and/or Python.

Bonus Qualifications:

  • Experience with deep learning software like TensorFlow or Pytorch.
  • Hands on experience with data processing and analysis.
  • Familiarity with chemistry / chemical sensing.

Duration: 3–6 months

How to apply

Candidates must have the legal right to work in the U.S.A.​ Please add Cover Letter and CV in the same document

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