Data Scientist

Fuse; San Leandro (CA); On-site; USD 145,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

Relocation assistance

Flexible time off

2 weeks of paid time off at year end

Leave for new parents

Job summary

Fuse, based in California, seeks a deep expert to build and evolve our in-house fusion simulation stack. You will model pulsed-power, radiation, and diagnostics, moving beyond curve fits to physics-based predictions that scale for research and operations.

This hands-on role requires a PhD and strong coding in Python and legacy C++/Fortran, with a track record in HPC workflows, Bayesian uncertainty analysis, and scalable simulations.

Qualifications

• PhD in Physics, Applied Mathematics, Plasma Physics, Computational Science, Nuclear Engineering, or a closely related field. An exceptional Master's candidate with a strong publication record will be considered.
• Strong academic record with a high GPA from a competitive program.
• Depth in at least one: magnetohydrodynamics, kinetic plasma theory, radiation transport, or pulsed-power circuit modeling.
• Fluency in vector and tensor calculus, Maxwell's equations, Bayesian statistics, and optimization under constraints.
• Production-grade Python with NumPy/SciPy/xarray/JAX/PyTorch; comfortable with C++ or Fortran when needed.
• Experience writing simulation code from scratch; ability to read a physics paper and assess applicability.

Responsibilities

• Build a coupled simulation framework for pulsed-power, plasma dynamics, and neutron/x-ray production.
• Implement radiation source-term models and surrogate/reduced-order models for fast parameter sweeps.
• Develop data pipelines integrating diagnostics and predicted outputs for residual analysis.
• Quantify uncertainty with Bayesian inference and identifiability analysis.
• Simulate machine outputs like electrode lifetimes and capacitor-bank aging to guide operations.

Skills

PhD in Physics

HPC experience

Python (NumPy/SciPy)

C++/Fortran

Magnetohydrodynamics

Radiation transport

Bayesian statistics

Modeling from physics data

Education

PhD in Physics/Applied Math/Plasma Physics/Nuclear Eng

Exceptional Master's with strong publication

Tools

NumPy/SciPy/xarray

JAX/PyTorch

C++/Fortran

GPU/HPC toolchains (SLURM)

Job description

About Fuse

We are building one of the most potentially consequential companies of the century. Our mission is to accelerate the world's transition to fusion energy while safeguarding humankind. This is not a normal company. This is not a normal job. We are committed for the long term to win.

About Fuse

We are building one of the most potentially consequential companies of the century. Our mission is to accelerate the world's transition to fusion energy while safeguarding humankind. This is not a normal company. This is not a normal job. We are committed for the long term to win.

About The Role

You will build our in-house simulation stack - the models that predict what our fusion machines will do, and the inference machinery that pulls physics out of shot data. This is not a "fit a curve to a dashboard" data science role.

Core Responsibilities

• Build a coupled simulation framework for our DPF: pulsed-power circuit, sheath formation and run-down (snowplow / slug / Lee-type models, progressing toward MHD), pinch and instability development, and neutron and X-ray production.
• Implement radiation source-term models: thermonuclear vs. beam-target neutron-yield decomposition, bremsstrahlung and line-emission spectra, and anisotropy.
• Develop surrogate and reduced-order models so designers and physicists can iterate on parameter sweeps without standing up an HPC job each time.
• Build the data pipeline that ingests every shot's diagnostic stream, including Rogowski coils, B-dots, silver activation, time-of-flight neutron detectors, filtered diodes, and fast cameras, and joins it to predicted output for systematic residual analysis.
• Quantify uncertainty seriously: Bayesian inference over model parameters, identifiability analysis, and honest error bars on yield predictions.
• Stand up simulations of supporting machine outputs, including anode/cathode lifetimes, electrode erosion models, and capacitor-bank aging, so operations decisions are informed by physics rather than vibes.
• Publish internally with the same standards you'd publish externally: derivations written out, assumptions stated, code reviewed.
• Eventually grow a small simulation team. For now, you will be a force multiplier of one.

Minimum Qualifications

• PhD in Physics, Applied Mathematics, Plasma Physics, Computational Science, Nuclear Engineering, or a closely related field. An exceptional Master's candidate with a strong publication record will be considered.
• Strong academic record, with a target GPA of 3.8+ from a competitive program.
• Demonstrable depth in at least one of: magnetohydrodynamics, kinetic plasma theory, radiation transport, or pulsed-power circuit modeling. Familiarity with the others.
• Fluency in vector and tensor calculus, Maxwell's equations in arbitrary geometries, hyperbolic PDEs and numerical schemes, Bayesian statistics, and optimization under constraints.
• Production-grade Python using NumPy, SciPy, xarray, JAX, or PyTorch for differentiable physics, with comfort dropping into C++ or Fortran when Python isn't fast enough.
• Experience writing simulation code from scratch, not just running someone'else's solver.
• Ability to read a physics paper, identify the load-bearing assumption, and determine quickly whether it applies to our regime.

Preferred Qualifications

• Hands-on experience with one or more of: MCNP, GEANT4, FLUKA, PIC codes such as LSP, EPOCH, or WarpX; MHD codes such as USim, FLASH, or HYDRA-class; or DPF-specific codes such as Lee model or GORGON-adjacent work.
• Prior work fitting models to noisy experimental diagnostics, including neutron TOF, X-ray spectroscopy, or magnetic-probe arrays.
• HPC experience including SLURM, MPI, GPU acceleration, and profiling at scale.
• Familiarity with the DPF literature or adjacent fields such as Z-pinch, MagLIF, or ICF, and a track record of getting up to speed quickly.
• Strong software-engineering hygiene: version control, tests for numerical code, and reproducible environments.

What We Value

• Give a shit. Build things you're proud of.
• Take responsibility. If something is broken and you can fix it, fix it. See things through.
• Move fast. Make decisions, learn quickly, and keep moving forward.
• Think bigger. Simplify relentlessly. Don't default to the safe answer.
• Disagree and commit. The best idea wins. Once a decision is made, we move.
• Desire to win. This is hard. Expect intensity. We are here to win.
• Plan B is to make Plan A work.

Additional Requirements

This is not a remote position and will require relocation if not already local to the applicable Fuse facility.

Benefits

• Medical, dental, and vision coverage.
• Relocation assistance for roles that require it.
• Flexible time off. Take what you need, no accrual tracking.
• 2 weeks of paid time off built into the end of each year, subject to team and business needs.
• Supportive leave of absence policies.
• Paid leave for new parents.

ITAR Requirements

To conform to U.S. Government technology export regulations, including the International Traffic in Arms Regulations (ITAR), you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.

Equal Opportunity

Fuse is an Equal Opportunity Employer; employment with Fuse is governed on the basis of merit, competence, and qualifications and will not be influenced by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, ancestry, immigration status, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.

Compensation Range: $145K - $190K