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Computational Materials Engineer

Phaseshift Technologies

Phaseshift Technologies

Toronto, ON, Canada · Toronto, ON, Canada · Ontario, Canada
Posted on Friday, April 26, 2024

Please forward your Resume and Cover Letter to hiring@thephaseshift.com. We will review only the applications received in the email.

Job Title: Computational Materials Engineer

About Us:

PhaseShift is advancing the materials industry by designing and commercializing new and innovative materials, including alloys and ceramics. Our in-house-developed computational platform leverages AI to rapidly design and optimize new materials, fundamentally accelerating the pace of innovation in new materials development. This streamlined approach significantly reduces R&D time and costs, allowing us to explore a broader range of opportunities than traditional methods allow.

The materials we develop play a crucial role in addressing key technological and environmental challenges across various industries, from aerospace to energy. By facilitating the development of more efficient and sustainable materials, our work supports industry advancements that lead to products and solutions that are better performing, more efficient, more cost-effective, and more sustainable.

We believe in our technology, which is why we use it internally to develop our own materials. Our commercial strategy involves collaborating with manufacturers and licensing our innovation to ensure these novel materials reach the market effectively, maximizing their impact.

Role Overview:

We are seeking a highly motivated Computational Materials Engineer to expand and enhance our computational platform, which focuses on designing and optimizing new engineering materials such as alloys, ceramics, and their composites. In this role, you will employ the Finite Element Method (FEM) and other advanced simulation tools to develop custom and highly specialized models that simulate the properties and behaviours of materials in various processes, including but not limited to Additive Manufacturing, Sintering, and Casting. These models will be integrated with our AI-based optimization algorithms to develop materials tailored for specific processes and targeted performance outcomes. This position is essential for translating theoretical designs into practical, manufacturable solutions that drive innovation in materials science.

Responsibilities:

  • Develop and optimize models to simulate metallurgical processes using Finite Element Method (FEM).
  • Utilize various FEM software packages such as Abaqus, ANSYS, and COMSOL for process simulation and optimization.
  • Engage in phase-field modelling and thermodynamic modelling to facilitate material design.
  • Manage and execute large-scale simulations using High-Performance Computing (HPC) with parallel computing architectures.
  • Customize FEM codes and build custom modules tailored to specific project requirements.
  • Communicate complex technical concepts and results effectively to team members, external collaborators, and clients.

Required Qualifications:

  • Master’s degree (or equivalent) in materials engineering, mechanical engineering, or a related discipline.
  • Proficiency in using FEM for metallurgical process modelling.
  • Extensive experience with various FEM software packages.
  • Strong background in phase-field and thermodynamic modelling.
  • A solid understanding of the composition-process-structure-property relationships in engineering materials is crucial for effective material design and optimization.
  • High proficiency in High-Performance Computing for scalable simulations.
  • Excellent coding skills in Python.
  • Outstanding oral and written communication skills, capable of conveying complex technical details clearly and effectively.

Desirable Qualifications:

  • PhD in process modelling with peer-reviewed publications.
  • Experience with atomistic simulation techniques like Molecular Dynamics (MD) and Density Functional Theory (DFT).
  • Knowledge of Data Science and Machine Learning applications in materials engineering and process modelling.
  • Industrial experience in process modelling of Additive Manufacturing, Casting, and/or Sintering.
  • Experience working in collaborative projects with experimentalists.
  • Familiarity with high-performance computing (HPC) resources and an understanding of cloud infrastructure like AWS or Azure.
  • Familiarity with Linux-based command-line operating systems.

Benefits:

  • Competitive Compensation Package: Attractive salary and potential for stock options, giving you a share in our success.
  • Health Benefits: A comprehensive health care plan that includes Medical, Dental, Vision, and Mental Health support ensures a holistic approach to health and well-being.
  • Paid Time Off: Generous leave policies include vacation, sick days, and public holidays, promoting work-life balance.
  • Professional Development: Dedicated budgets for skill enhancement, including conferences, workshops, and additional training tailored to your interests and career goals.
  • Flexible Working Conditions: Remote work options and flexible hours to accommodate your lifestyle and increase productivity.
  • Innovative Culture: Join a team that values innovation and is open to ideas that challenge the norm.
  • Dynamic Environment: Fast-paced and agile workplace that allows you to see the impact of your work directly and quickly.
  • Access to Cutting-Edge Technology: Work with the latest technologies and tools in materials science and computational modelling.
  • Collaborative Atmosphere: Close collaboration with a small, passionate team allows for hands-on contributions to projects that make a difference.
  • Sense of Ownership: Take ownership of your projects with the opportunity to grow into decision-making roles as you demonstrate your capabilities and help shape the company's future.

Join Us:

If you're passionate about pushing the boundaries of materials engineering and enjoy working in a dynamic environment to solve complex problems that have the potential to create real-world impact, apply now to help us drive the future of material science.