Innovation Associate in Machine Learning (Postdoctoral Fellow)

Updated: 3 months ago
Job Type: FullTime
Deadline: 14 Aug 2020

Algolysis Ltd (www.algolysis.com ) is seeking to recruit an experienced Researcher in Machine Learning (R2/R3) who will lead the development of reinforcement learning methodologies for failure prediction on storage devices monitored by our flagship DriveNest (www.drivenest.com ) platform. DriveNest is a sophisticated, platform for monitoring hundreds of thousands of computer storage devices aiming to prevent data losses by utilizing crowd-sourced device metrics for early failure detection.

The successful candidate will devise sophisticated predictive models, using Reinforcement and/or Deep Learning, to accurately identify soon-to-fail storage devices. The activities to be carried out will cover all the stages of the ML learning lifecycle, i.e. specifying the challenge, data preparation, (multi) model specification, training and evaluation, and an experimental accuracy evaluation over unknown data.

This is a 12-month, Full-time position with a competitive salary and a relocation package supported through the competitive European SME Innovation Associate programme (INNOSUP-02-2019-2020). Subject to performance during the 12-month contract, Algolysis may offer a long-term employment to the successful candidate.

The selected candidate is expected to fit the following profile:

  • Experienced researcher (R2/R3) specializing in Machine Learning
  • Experience in Deep and/or Reinforcement Learning, predictive analytics or anomaly detection
  • Innovative thinker and good communicator
  • A team player with the desire to teach others and learn from others
  • Aspiration to gain business skills and innovate in the industry

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