About the role
Fusionality is building the measurement, simulation, and control stack for the fusion energy reactors of the future.
Spun out of EPFL’s Swiss Plasma Center and backed by top investors, our technology enables reliable operation, real-time monitoring, and analysis of high-temperature plasmas in fusion devices. We are founded by world-class experts at the intersection of fusion physics, advanced control, and AI (ex-Google DeepMind, EPFL). We are assembling a founding engineering team in Lausanne to build our core technology platform.
We are looking for a Computational Scientist specialized in Scientific Machine Learning (SciML) to join our team. This job is for you if you know how to write numerical solvers that are fast, correct and differentiable end to end, and want to see them run against real plasma data and inside real control systems.
We are looking for a PhD-level or senior computational researcher for this role.
Responsibilities
Design, implement and validate differentiable solvers in JAX for plasma physics problems such as free-boundary equilibrium, transport and state estimation.
Make them robust and fast enough for production use via advanced numerical techniques for differential equation time stepping, as well as optimization of GPU/TPU performance.
Using automatic differentiation for model calibration against experimental data, parameter estimation and controller design and optimization, working with our data and control engineers.
Code ownership: quality, testing, verification against reference solutions, packaging and documentation.
Requirements
Substantial code written in a differentiable framework. Our stack is in JAX, Julia or PyTorch experts are very welcome if they’re happy to switch.
Strong background in numerical methods for ODEs and PDEs: discretisation, stiff and implicit solvers, nonlinear and sparse linear solvers.
Demonstrated ability to operate at the frontier of SciML, Universal Differential Equations, Neural ODEs, and other emerging hybrid data-driven/mechanistic paradigms.
Evidence of independent work at the highest level: a PhD or thesis, published code that is used by others, or an industry project you owned.
Proficient using Agentic coding and other modern AI technologies to accelerate your work, while remaining accountable for the results.
Experience in the following fields an advantage but not strictly required:
The JAX ecosystem: Diffrax, Equinox, Optax, Lineax.
Plasma, fluid, electromagnetic, or other multiphysics simulation.
Having led the design of a scientific codebase used by others.
What we offer
Play a key role at a dynamic, fast-growing startup, shaping the technical solutions and products from the ground up.
Build cutting-edge technology to monitor and control plasmas in real fusion devices, working side-by-side with leading plasma and control experts.
Great working conditions, located in Lausanne, Switzerland, a city and country known for its high quality of life.
Competitive salary and equity compensation and benefits including immigration assistance.
Find Jobs in Switzerland on Arbeitnow
Spun out of EPFL’s Swiss Plasma Center and backed by top investors, our technology enables reliable operation, real-time monitoring, and analysis of high-temperature plasmas in fusion devices. We are founded by world-class experts at the intersection of fusion physics, advanced control, and AI (ex-Google DeepMind, EPFL). We are assembling a founding engineering team in Lausanne to build our core technology platform.
We are looking for a Computational Scientist specialized in Scientific Machine Learning (SciML) to join our team. This job is for you if you know how to write numerical solvers that are fast, correct and differentiable end to end, and want to see them run against real plasma data and inside real control systems.
We are looking for a PhD-level or senior computational researcher for this role.
Responsibilities
Design, implement and validate differentiable solvers in JAX for plasma physics problems such as free-boundary equilibrium, transport and state estimation.
Make them robust and fast enough for production use via advanced numerical techniques for differential equation time stepping, as well as optimization of GPU/TPU performance.
Using automatic differentiation for model calibration against experimental data, parameter estimation and controller design and optimization, working with our data and control engineers.
Code ownership: quality, testing, verification against reference solutions, packaging and documentation.
Requirements
Substantial code written in a differentiable framework. Our stack is in JAX, Julia or PyTorch experts are very welcome if they’re happy to switch.
Strong background in numerical methods for ODEs and PDEs: discretisation, stiff and implicit solvers, nonlinear and sparse linear solvers.
Demonstrated ability to operate at the frontier of SciML, Universal Differential Equations, Neural ODEs, and other emerging hybrid data-driven/mechanistic paradigms.
Evidence of independent work at the highest level: a PhD or thesis, published code that is used by others, or an industry project you owned.
Proficient using Agentic coding and other modern AI technologies to accelerate your work, while remaining accountable for the results.
Experience in the following fields an advantage but not strictly required:
The JAX ecosystem: Diffrax, Equinox, Optax, Lineax.
Plasma, fluid, electromagnetic, or other multiphysics simulation.
Having led the design of a scientific codebase used by others.
What we offer
Play a key role at a dynamic, fast-growing startup, shaping the technical solutions and products from the ground up.
Build cutting-edge technology to monitor and control plasmas in real fusion devices, working side-by-side with leading plasma and control experts.
Great working conditions, located in Lausanne, Switzerland, a city and country known for its high quality of life.
Competitive salary and equity compensation and benefits including immigration assistance.
Find Jobs in Switzerland on Arbeitnow
Requirements
- Data Scientist