Senior Research Scientist, Magnets

About the role

SandboxAQ is building AI‑driven computational chemistry platforms to discover new materials. The Magnets team focuses on designing high‑performance permanent magnets that reduce reliance on rare‑earth elements and can be manufactured in the United States. As a Senior Research Scientist you will lead computational discovery and optimization of next‑generation magnet formulations.

Key responsibilities

• Run and interpret DFT and multi‑scale simulations to predict phase stability, magnetocrystalline anisotropy, saturation magnetization, Curie temperature and related properties of Fe‑ and Co‑based intermetallic systems.
• Develop and deploy high‑throughput computational and ML workflows, including interatomic potentials and surrogate models, to screen rare‑earth‑lean and rare‑earth‑free magnet candidates.
• Coordinate data‑generation campaigns that feed the magnetism‑aware Large Quantitative Model (LQM) and define required energetics, descriptors and uncertainty estimates.
• Link atomistic outputs to microstructure and process‑level predictions (powder metallurgy, sintering, heat treatment) to ensure manufacturability with existing industry equipment.
• Collaborate with experimental partners to validate predictions, iterate on models, and contribute to the Design‑Build‑Test‑Learn feedback loop.

Required profile

• PhD (or equivalent) in solid‑state physics, quantum chemistry, materials science or a related discipline.
• Hands‑on experience with DFT or atomistic simulation and strong Python programming skills.
• Demonstrated ability to apply machine learning, surrogate modeling or high‑throughput methods to materials problems.
• Experience collaborating with experimental or cross‑functional teams to validate computational predictions.
• U.S. Person status (permanent resident or citizen) due to government contract requirements.

Required skills

• Density Functional Theory (DFT) and atomistic simulation tools (e.g., VASP, Quantum ESPRESSO, LAMMPS, ASE).
• Machine‑learning frameworks and interatomic potentials (e.g., MACE, NequIP, Allegro, FairChem, PyTorch, JAX).
• High‑performance computing (HPC) and cloud environments.
• Python programming and modern scientific‑computing practices.
• Bayesian optimization, active learning, and autonomous discovery workflows.

What we offer

• Competitive base salary, equity and performance‑based incentives.
• Comprehensive health, dental and vision insurance, 401(k) with company match, and generous parental leave.
• Flexible hybrid work arrangements, generous PTO and a culture that respects focus time.
• Direct exposure to CHIPS‑Act funded programs, senior scientific leadership, mentorship and dedicated learning budgets.