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Fuse is building fusion energy technology with a mission to accelerate the world's transition to fusion while safeguarding humankind. This Data Scientist role focuses on building the in-house simulation stack that predicts fusion machine behavior and extracts physics from experimental shot data.
You will own the full lifecycle of physics-based modeling: developing coupled simulation frameworks for the Dense Plasma Focus (DPF) device, including pulsed-power circuits, plasma sheath formation, pinch dynamics, and neutron/X-ray production. You'll implement radiation source-term models covering thermonuclear and beam-target neutron yields, bremsstrahlung, line-emission spectra, and anisotropy effects.
Key responsibilities include building surrogate and reduced-order models to enable rapid parameter sweeps without HPC overhead, constructing data pipelines that ingest multi-modal diagnostics (Rogowski coils, B-dots, silver activation, time-of-flight neutron detectors, filtered diodes, fast cameras), and performing systematic residual analysis. You will quantify uncertainty rigorously through Bayesian inference, identifiability analysis, and honest error quantification on yield predictions.
Additionally, you'll develop supporting simulations for machine outputs like anode/cathode lifetimes, electrode erosion, and capacitor-bank aging to inform operations decisions. Work is published internally to external standards with full derivations, stated assumptions, and code review. Over time, you may grow a small simulation team, but initially you operate as a force multiplier of one.
This is a hands-on role requiring deep physics expertise and production-grade software engineering. You will read physics papers, identify load-bearing assumptions, and rapidly determine applicability to Fuse's regime. ITAR compliance required; U.S. citizenship or lawful permanent residency mandatory.
