Research Scientist, Materials Characterization
$225,000 - $325,000 per year
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Posted today
SENIORITY
Lead
SALARY
$225,000 - $325,000 per year
About the role
- Develop and perform high-fidelity thermodynamic, transport, and spectroscopic measurements of materials, including electronic, magnetic, and thermal properties
- Design and implement rapid property measurement schemes to scale up the material characterization process and feed AI-guided discovery pipelines
- In collaboration with the AI team, implement automated data analysis and reasoning pipelines for screened materials; contribute to feedback loop design between measurement and prediction
- In collaboration with the engineering team, develop autonomous systems for property characterization leveraging robotics and programmable instrumentation
- Evaluate, procure, and commission new instrumentation; develop custom measurement setups where commercial solutions are insufficient
- Define and enforce data standards, metadata schemas, and documentation practices to ensure measurement outputs are reproducible and reusable
- Uphold and contribute to lab safety standards, particularly around cryogenic systems, high-field magnets, and hazardous materials
- You Will Thrive in This Role If You HavePhD in Physics, Materials Science, or related field, with 5+ years of hands-on experience in physical property characterization
- Deep, demonstrated expertise in electronic and magnetic property measurements, including resistivity, Hall effect, magnetometry, and heat capacity
- Strong background in cryogenic measurements and low-noise techniques, including lock-in methods, shielding/grounding, and precision instrumentation
- Strong track record of highly impactful research demonstrated by publications in top-tier journals and/or inventions, and recognized leadership in the field
- Proficiency with data analysis (e.g., Python/Jupyter, familiarity with instrument SDKs a plus) and disciplined data management practices
- Excellent scientific writing, cross-disciplinary collaboration, and strong ownership of experiment quality
- Ability to communicate measurement requirements and findings clearly to AI, engineering, and materials science collaborators
- Especially Strong Candidates May Also Have
- Experience with automation of physical property measurement platforms (e.g., PPMS, MPMS, custom rigs)
- Experience with the computational prediction and experimental characterization design loop
- Experience with spectroscopic characterization techniques such as ARPES, neutron scattering, or optical spectroscopy
- Experience with lab buildout, instrument commissioning, and process safety
- Experience handling and managing data at scale, including LIMS or similar data infrastructure
- Previous work at national laboratories or large-scale user facilities
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