Senior Research Scientist, Magnets

The role

You will drive the computational discovery and optimization of next-generation magnet materials. This involves running atomistic and multi-scale simulations, building ML-driven workflows, and collaborating with experimentalists to refine predictions.

What you will do

• Execute, analyze, and document DFT and multi-scale reference systems to predict material properties.
• Develop and test computational workflows and ML interatomic potentials for high-throughput screening.
• Lead high-fidelity data generation campaigns to feed the magnetism-aware LQM.
• Connect atomistic simulation outputs to microstructure- and process-level predictions.
• Collaborate with experimental validation partners to iterate on model predictions.
• Work within agile, multidisciplinary teams to generate and evaluate hypotheses.
• Communicate research findings through scientific talks, publications, and patents.
• Support junior scientists and interns.

Required qualifications

• PhD or equivalent experience in Solid-state Physics, Quantum Chemistry applied to Materials Science or a related field.
• Hands-on experience with DFT or atomistic simulation.
• Strong programming skills in Python and modern scientific-computing practices.
• Experience applying machine learning, surrogate modeling, or high-throughput methods to materials problems.
• Demonstrated ability to collaborate with experimental or cross-functional teams to validate and iterate on predictions.

Nice to have

• Specialization in alloys, microstructure engineering, magnetism, intermetallics, or hard/functional magnetic materials.
• 3+ years of hands-on experience (post-PhD or equivalent) applying DFT and atomistic simulation specifically to magnetic, intermetallic, crystal lattices, energy bands, or phonons for material science.
• Proficiency with common DFT and atomistic simulation software (e.g., VASP, Quantum ESPRESSO, LAMMPS, ASE).
• Experience developing or using ML interatomic potentials and AI models for materials discovery (e.g., MACE, NequIP, Allegro, or FairChem) with modern deep learning frameworks (e.g., PyTorch, JAX), and
• Hands-on experience with Fe-N, Mn-based, Sm-Co, or other rare-earth-lean permanent magnet systems and their bulk processing challenges.
• Experience with finite-temperature magnetism and coercivity modeling, including atomistic spin dynamics and/or micromagnetic simulation.
• Familiarity linking composition and microstructure to processing and application requirements.
• Familiarity with Bayesian optimization, active learning, or autonomous discovery workflows applied to materials.
• Authorship of publications in high-impact peer-reviewed journals, and/or patents, in magnetic materials, computational chemistry, or AI for materials science.
• Experience operating within CHIPS Act, DOD, DOE, or other federally funded R&D programs.

Benefits

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

Before you apply

• We can only consider US Persons (Permanent Residents or Citizens) at this time.

About the company

SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022.