Remote R&D Engineer – CFD & Solver Innovation

Remote R&D Engineer – CFD & Solver Innovation

Full-Time 50000 - 70000 Β£ / year (est.) No working from home possible
Synopsys, Inc.

At a Glance

  • Tasks: Enhance fluid dynamics simulation tools and develop solvers in Python and Fortran.
  • Company: Join Synopsys, a leader in innovative technology solutions.
  • Benefits: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
  • Other info: Collaborate with a focused team of R&D engineers in a dynamic environment.
  • Why this job: Make a real impact on renewable energy through advanced simulation solutions.
  • Qualifications: Strong expertise in numerical methods and fluid dynamics required.

The predicted salary is between 50000 - 70000 Β£ per year.

Synopsys, Inc. in the UK is looking for a Staff Engineer to enhance fluid dynamics simulation tools. This role involves developing solvers in Python and Fortran and requires strong expertise in numerical methods and fluid dynamics.

As part of a focused team of R&D engineers, you'll contribute to optimizing simulation capabilities, enabling innovative marine and offshore applications. The role supports the transition to renewable energy through advanced simulation solutions.

Remote R&D Engineer – CFD & Solver Innovation employer: Synopsys, Inc.

At Synopsys, Inc., we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our remote R&D Engineer role offers not only competitive benefits but also ample opportunities for professional growth in the cutting-edge field of fluid dynamics simulation. Join us in our mission to support renewable energy initiatives while working alongside a dedicated team of experts in a flexible and supportive environment.

Synopsys, Inc.

Contact Details:

Synopsys, Inc. Recruitment Team

We think you need these skills to ace Remote R&D Engineer – CFD & Solver Innovation

Python
Fortran
Numerical Methods
Fluid Dynamics
Simulation Tools Development
R&D Engineering
Optimisation Techniques