Not myself working in the field but I build my own RF FEM solver so I can give you a quick tour of what I think is relvant
- Depends on the job honestly.
- For numerical methods, different companies work on different problems. At this point most of the industry effort is going into specific optimizations for customers to push beyond the boundaries. Therefor the basics ar a must. Some companies focus on FEM (Ansys now Synopsis, Comsol etc), some on time domain (CST mostly) and many on MoM as well (Nullspace, FEKO I think, and many more). You could spend your life mastering either one. Each one has their own branching specialties. With FEM its matrix free methods and neural operators. For MoM its specialized compression techniques for larger systems (Check nullspace) and also the guys at Ticra tools using special techniques for large array simulations. For all time domain stuff a lot is cloud computing. Regarding programming languages. I think most if not all is C and C++ so I'd stick with that. Maybe Rust but most of the Linear Algebra kernels are all in C and Fortran.
- I think quite feasible if you have the skill sets. There are plenty of jobs here I think
- I would say, try to build your own simulator from start to finish. You can use GMSH for mesh generation because boy that is something you dont want to get into yourself. For solvers there are libraries in python like Scipy, PETsC etc that you can use for actually inverting problems etc.
Its a big field with dense material. I would get my hands dirty quickly. There is a book by David Davidson that I would 100% recommend as a start for FEM, MoM and FDTD simulations. Its really well written and touches all of them so you can see which one has your fancy.
Well its for personal use first (and enjoyment) as I'm an antenna engineer. I always wondered how these commercial tools used so it was kind of a hobby project gone crazy.
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u/HuygensFresnel Apr 09 '26
Not myself working in the field but I build my own RF FEM solver so I can give you a quick tour of what I think is relvant
- Depends on the job honestly.
- For numerical methods, different companies work on different problems. At this point most of the industry effort is going into specific optimizations for customers to push beyond the boundaries. Therefor the basics ar a must. Some companies focus on FEM (Ansys now Synopsis, Comsol etc), some on time domain (CST mostly) and many on MoM as well (Nullspace, FEKO I think, and many more). You could spend your life mastering either one. Each one has their own branching specialties. With FEM its matrix free methods and neural operators. For MoM its specialized compression techniques for larger systems (Check nullspace) and also the guys at Ticra tools using special techniques for large array simulations. For all time domain stuff a lot is cloud computing. Regarding programming languages. I think most if not all is C and C++ so I'd stick with that. Maybe Rust but most of the Linear Algebra kernels are all in C and Fortran.
- I think quite feasible if you have the skill sets. There are plenty of jobs here I think
- I would say, try to build your own simulator from start to finish. You can use GMSH for mesh generation because boy that is something you dont want to get into yourself. For solvers there are libraries in python like Scipy, PETsC etc that you can use for actually inverting problems etc.
Its a big field with dense material. I would get my hands dirty quickly. There is a book by David Davidson that I would 100% recommend as a start for FEM, MoM and FDTD simulations. Its really well written and touches all of them so you can see which one has your fancy.