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Computational Engineer

Proxima Fusion
CompanyProxima Fusion
CategoryEngineering
LocationMunich
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted8 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
WHO WE ARE Proxima Fusion is Europe’s fastest-growing fusion company and the continent’s best-funded fusion player, as well as the first spin-out from the Max Planck Institute for Plasma Physics (IPP). Backed by over €650M and powered by a growing team across Munich, Zurich, and Oxford, we are developing the hardware and infrastructure needed to deliver the world’s first commercial stellarator fusion power plant. Our concept advances the most mature fusion technology out there, the Wendelstein 7-X stellarator, through two next-generation machines: Alpha and Stellaris. Our work combines stellarator optimization, advanced computation, machine learning, and high-temperature superconducting magnets to unlock higher-performance designs that were previously out of reach. Turning these designs into a functioning fusion power plant requires excellence and ownership across every discipline, from physics and engineering to software, manufacturing, law, and business functions. TEAM & ROLE - Shape the architecture of the world’s first commercial fusion power plant – Own system-level decisions that determine how a first-of-a-kind energy technology is designed, integrated, and ultimately deployed at scale. - Solve some of the most complex engineering challenges in industry – Work across tightly coupled disciplines (plasma physics, magnets, cryogenics, manufacturing, controls, and more) to resolve critical trade-offs and turn cutting-edge science into a functioning product. - Build real hardware with a pragmatic, fast-moving team from all over the world – Combine advanced simulation and systems thinking with a strong execution mindset, focusing on practical engineering solutions that accelerate the path to commercial fusion energy. WHY JOIN PROXIMA FUSION - You will get to work on some of the most complex tech challenges to bring abundant, safe, clean energy to the world. - You'll get to join and learn from an exceptional selection of accomplished and driven individuals. - Do your life’s best work and enjoy the journey. - Get to show that big things are possible in Europe when you assemble the best talent. YOUR IMPACT Our approach to stellarator design is rooted in parametric design defined in code, differentiable models, and fully automated analysis pipelines. It is a departure from how complex machines have historically been engineered. As a Computational Engineer, you will be a key contributor to this approach. You will own the software that defines stellarator geometry, automates multi-physics analysis, and makes complex 3D shapes optimisable. You'll use your combined understanding of engineering and computation to push the boundaries of what can be designed. You will develop new geometric representations, formulate optimisation problems, and find solutions to engineering challenges that don't have textbook answers. Sitting at the intersection of mathematics, software, and mechanical engineering, you will have direct influence over the design of the machine itself. WHAT YOU WILL DO - Define stellarators in code. Create parametric representations of reactor components; covering everything from plasma-facing walls to superconducting cables. - Automate engineering analysis. Own the code path from parametric description to CAD (e.g. CadQuery) to mesh (e.g. Gmsh) to simulation to post-processing, all running in the cloud. - Architect integrated systems. Use your ability to develop and leverage powerful computational tools to understand the trade-offs across sub-systems. - Make designs differentiable. Build JAX-based geometric and physics models so that you can optimise quantities like coil clearances, structural loads, and manufacturing constraints with gradient-based methods. - Implement algorithms for our custom 3D geometries (e.g. signed distance functions, kd-tree spatial queries, adaptive sampling, and collision detection). - Work across teams and disciplines. Collaborate
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