Computational Engineer

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. 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.

Responsibilities

Architect integrated systems. Use your ability to develop and leverage powerful computational tools to understand the trade-offs across sub-systems.; 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 to mesh to simulation to post-processing, all running in the cloud.; Work across teams and disciplines. Collaborate directly with other mechanical engineers and simulation specialists to design key components (e.g. HTS magnets).; 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.; Write new algorithms for our custom 3D geometries (e.g. signed distance functions, kd-tree spatial queries, adaptive sampling).

Requirements

An exceptionally capable early-career engineer who enjoys solving difficult technical problems and naturally reaches for code to do so.; The ability to reason from first principles and make progress on problems that are initially ambiguous or poorly defined.; Strong fundamentals in linear algebra and geometry.; Experience using Python to solve engineering or scientific problems.; Comfort with Git and an appreciation for well-tested, well-typed, maintainable code.; Excellent communication skills.; A foundation of relevant experience, which may include internships, student engineering teams, open-source work, or substantial independent projects.

Benefits

Work on some of the most complex tech challenges to bring abundant, safe, clean energy to the world.; 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.