Date: May 28, 2021

Location: Montreal, Quebec, CA, H4M 2Z2

Company: iBwave

Please note: iBwave is a wholly-owned subsidiary of Corning. As a Fortune 500 leader in advanced glasses and ceramics development for over a century, Corning Inc overcomes challenging engineering problems continually. The Advanced Analytics and Machine Learning Group within the Corning Technology Center, Montreal (CTCM) is a team of scientists, engineers and software developers working on broad-spectrum machine learning and data science solutions to enable some of the most exciting industrial innovations of our time.


We are looking for a talented and motivated Machine Learning and Analytics Engineer focusing on physics-based machine learning You will drive a number of Corning initiatives in data-driven physics modeling.


  • Develop data-driven physical predictive models within R&D and manufacturing
  • Work on all aspects of the analytics solution development from building efficient data pipelines to implementing leading-edge inferential methods
  • Deploy scalable solutions for large datasets • Develop high-performance software solutions, primarily with the Python data-science stack, and using compiled languages such as C/C++, Fortran, C#, Java
  • Work in collaboration with project management to deliver effective and timely solutions
  • Interact regularly with research groups within Corning
  • Stay abreast of new developments in the field of physics-informed machine learning, with a constant eye on how these innovations can be applied to our problems
  • Participate in presenting new results and research innovations internally and externally
  • Cultivate and grow ties with academia
  • Mentor new hires and interns

WHAT WE ARE LOOKING FOR – if you have it, let’s talk.

  • Strong background in numerical modeling and emerging machine learning and deep learning methods applied to numerical modeling in mechanical engineering, chemical engineering, materials science and applied physics.
  • Experience demonstrated through industrial work, academic research projects or compelling open-source project contributions.
  • Deep understanding of one or more numerical modeling domains, including but not limited to: computational fluid dynamics and heat transfer, solid mechanics, computational materials science, computational electromagnetics, molecular dynamics, agent-based modeling, cellular automata.
  • Strong interest, and preferably demonstrated background, in emerging machine learning approaches to enable and accelerate numerical simulation of physics and chemistry.
  • Strong programming background in one or more languages such as C/C++, Fortran, Python, C#, Java.
  • Excellent communication skills – both oral and written.
  • Graduate-level training in numerical simulation in mechanical / chemical / electrical / civil / materials engineering, applied math, applied physics.
  • Strong hands-on experience with the Python data science stack (Python core, NumPy, SciPy, Pandas, Matplotlib, scikit-learn and deep learning frameworks such as Tensorflow or PyTorch).
  • Experience with High Performance Computing, including General Purpose GPUs, would be a strong asset.
  • Experience in writing clean and maintainable code is critical. Working as part of a team using source management frameworks such as GIT is an asset.


  • Autonomy (Self-starter)
  • Creativity
  • Detail-oriented and precision
  • Team player
  • Organized


iBwave is not accepting unsolicited assistance from search firms for this employment opportunity. Please, no phone calls or emails. All resumes submitted by search firms to any employee at iBwave via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of iBwave. No fee will be paid in the event the candidate is hired by iBwave as a result of the referral or through other means.